The present study investigated crack visualization in metallic structures using time-domain reflectometry with a two-dimensional microstrip line. 2D inspection was enabled by covering the inspected structure surface with the microstrip conductor to compensate for the lack of information in the transverse direction. Crack visualization experiments were conducted using the proposed TDR with single ended of 2D MSL for different crack length. The experimental results demonstrated that crack propagation could be clearly visualized. However, false cracks appeared at the same position regardless of the crack position. The electromagnetic field simulation results clarified that the false cracks observed in the experiments were caused by cross talk. The problem can be eliminated by arranging the microstrip conductor appropriately.
Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control
systems such as anti-lock braking systems (ABSs). However, since a conventional foil strain gage has high stiffness, it
causes the analyzed region to behave unnaturally. The present study proposes a novel rubber-based strain sensor
fabricated using photolithography. The rubber base has the same mechanical properties as the tire surface; thereby the
sensor does not interfere with the tire deformation and can accurately monitor the behavior of the tire. We also
investigate the application of strain data for an optimized braking control and road condition warning system. Finally, we
suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control
can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction
coefficient at a certain slip ratio is lower than a 'safe' reference value.
The present paper deals with a self-deployable graphite/epoxy composite structure using a partially flexible composite
(PFC) with shape memory alloy wires. The present paper introduces the fabrication processes of the PFC. Two different
matrices are used for the PFC: epoxy resin for the normal main part, and silicone rubber for the folding line. Since the
fibers are continuous in the structure, the PFC has the same tensile strength as a normal composite. We investigate
graphite fiber breakages during the folding process by considering changes in electrical resistance. An SMA wire is
embedded in the PFC to keep the folded configuration without loading and self-deployment is achieved using Joule
heating. The results confirm that a flexible part of adequate length enables foldable composite structures without causing
carbon fiber breakages. The embedded SMA wire realizes compactly folded composite panel structures without loading
and Joule heating of the SMA wires enables self-deployable composite structures.
KEYWORDS: Sensors, Roads, Finite element methods, Control systems, Safety, Chemical elements, Telecommunications, Intelligence systems, Wireless communications, Data modeling
From a traffic safety point-of-view, there is an urgent need for intelligent tires as a warning system for road conditions, for optimized braking control on poor road surfaces and as a tire fault detection system. Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control systems such as anti-lock braking systems (ABSs). In previous studies, we developed a direct tire deformation or strain measurement system with sufficiently low stiffness and high elongation for practical use, and a wireless communication system between tires and vehicle that operates without a battery. The present study investigates the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis. Finally, we suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction coefficient at a certain slip ratio is lower than a 'safe' reference value.
Since delamination is invisible or difficult to detect visually, the delamination causes low reliability of laminated
composites for primary structures. To improve the low reliability, smart systems of delamination identifications
in-service are desired. Recently, many researchers have employed an Electrical Resistance Change Method (ERCM)
to detect the internal damages of Carbon Fiber Reinforced Plastics (CFRP) laminates. The ERCM does not require
expensive instruments. Author's group has already experimentally investigated the applicability of the ERCM for
monitoring delamination crack and matrix cracks. In the present paper, therefore, these results performed in the previous
papers are briefly explained. These successful results enable us to monitor a lot of information of the CFRP laminates by
means of the electrical resistance changes in many applications. In these previous papers, the plate type specimens are
small. The effect of plate scale on ERCM is investigated in the present paper. 3-D FEM analyses are conducted to
calculate the electrical potential changes caused by delamination for CFRP plates of different sizes and the applicability
of ERCM to large CFRP structures is investigated.
For Unmanned aerial vehicles, a morphing wing is desired to improve the maneuverability and reduce the total weight
of structures. Our research group has developed a foldable composite structure for a morphing wing skin plate by using
Carbon Fiber Reinforced Plastics (CFRP). The material system is called Partially Flexible Composites (PFC). In the
present paper, PFC is introduced and a self-sensing system of the PFC is investigated. Since carbon fibers have
electrical conductivity, damages of the PFC can be detected by monitoring electrical resistance changes of the PFC.
This method is called Electrical Resistance Changes Method. An electrical resistance model of the PFC is built and a
relationship of ratio of fiber fractures and electrical resistance changes is obtained. Then, to investigate the
performance of the PFC, cyclic-bending tests are conducted. Damages of the PFC caused by cyclic-bending are
detected by using ERCM. As a result, the PFC with more than 10mm-long flexible part has almost no damage; the
stiffness of the structure remains unchanged. After that, a McKibben pneumatic artificial muscles actuator is made
and it is founded that this can be applied to the PFC as an actuator. This actuator consists of a silicon rubber and a
carbon fiber that are the same as the material of flexible part of the PFC. This enables us to make actuator-integrated
composite structures. In the present study, the applicability of the McKibben pneumatic artificial muscles actuator is
investigated.
Designs for future spacecraft have been conceived with very large lightweight apparatus and structures. New techniques
of packaging to be stowed into existing launch vehicles are desired. A kind of current deployment techniques is
mechanical hinge mechanisms and this results in an increase of weight in structures. In the present study, Partially-
Flexible CFRP with SMA embedded (PFC-S) is proposed to be appropriate for the deployable structures. The PFCS
consists of two kinds of matrices: high-stiffness resin matrix and low-stiffness rubber matrix, and the SMA are
embedded in low-stiffness rubber part. It can be deformed and folded for packaging and it can be deployed with over 80°C due to the SMA embedded. Since the width of PFCS influences the foldable shape, the relationship between width of
the PFCS and the curvature of foldable shape is investigated by using specimens with various width of flexible part. Also
the effect of SMA embedded and temperature change on bending stiffness in specimen is measured. As a result, it is
found that narrow PFCS specimen keeps appropriate shape with comfortable curvature, and SMA embedded and
elevated temperature increases bending modulus of the PFCS specimen.
KEYWORDS: Diagnostics, Fluctuations and noise, Sensors, Data modeling, System identification, Inspection, Damage detection, Structural health monitoring, Mechanical engineering, Finite element methods
For the health monitoring of existing structures, modeling of entire structure or obtaining data sets after creating damage for
training is almost impossible. This raises significant demand for development of a low-cost diagnostic method that does not
require modeling of entire structure or data on damaged structure. Therefore, the present study proposes a low-cost
statistical diagnostic method for structural damage detection. The novel statistical diagnostic method is a low cost simple
system. The diagnostic method employs system identification using a response surface and the damage is automatically
diagnosed by testing the change of the identified system by statistical F test. The statistical diagnostic method consists of a
learning mode and a monitoring mode. The learning mode is a preparation mode and is performed to create the standard of
the diagnosis. The monitoring mode is a diagnosis mode and is performed to diagnose the structural condition. In the
learning mode, reference data are measured from an intact structure. A reference response surface is calculated from the
reference data using the response surface method. In the monitoring mode, data are measured from a structure to diagnose
and a measured response surface is calculated. The statistical similarity of the reference response surface and the measured
response surface is tested using the F-test for the damage diagnosis. When the similarity of the response surfaces is adopted,
a conclusion of the diagnosis is intact condition. On the other hand, when the similarity is rejected, the diagnosis concludes
the structure was damaged. The system does not require the relation between measured sensor data and damages. The
method does not require a FEM model of the entire structure. This method diagnoses slight change of the relation between
the measured sensor data.
In this study, the health monitoring system of the jet fan was developed to investigate the effectiveness of the proposed
method. In this study, field test was conducted using an actual jet fan in a tunnel. In the field test, robustness of the proposed
method was investigated. As a result, the structural condition of the jet fan was successfully diagnosed and effectiveness of
proposed method was confirmed.
This paper examines damage monitoring for woven graphite/epoxy laminate by means of an electrical resistance change method. The method has been proposed by the authors and successfully applied to cross-ply and quasi-isotropic laminates; the method has yet to be applied to woven laminates. Therefore, a woven graphite/epoxy composite is selected for the target material of the electrical resistance change method to identify the damage. Beam type specimens consisting of woven laminates are the focus of this paper. The influence of a different electrical property of woven laminate upon the electrical resistance change is investigated both analytically and experimentally, and the condition of the electrical contact between the electrode and the specimen is investigated experimentally. For the purpose of identification, the response surface is adopted as a solving method for the inverse problem. As a result, the method shows excellent performance for estimating delamination locations and sizes.
In-service strain monitoring of tires of automobile is quite effective for improving the reliability of tires and Anti-lock Braking System (ABS). Since conventional strain gages have high stiffness and require lead wires, the conventional strain gages are cumbersome for the strain measurements of the tires. In a previous study, the authors proposed a new wireless strain monitoring method that adopts the tire itself as a sensor, with an oscillating circuit. This method is very simple and useful, but it requires a battery to activate the oscillating circuit. In the present study, the previous method for wireless tire monitoring is improved to produce a passive wireless sensor. A specimen made from a commercially available tire is connected to a tuning circuit comprising an inductance and a capacitance as a condenser. The capacitance change of tire causes change of the tuning frequency. This change of the tuned radio wave enables us to measure the applied strain of the specimen wirelessly, without any power supply from outside. This new passive wireless method is applied to a specimen and the static applied strain is measured. As a result, the method is experimentally shown to be effective as a passive wireless strain monitoring of tires.
The present research proposes a new automatic damage diagnostic method that does not require data of damaged state. Structural health monitoring is a noticeable technology for civil structures. Multiple damage diagnostic method for has been proposed, and most of them employ parametric method based on modeling or non-parametric method such as artificial neural networks. These methods demand much costs, and first of all, it is impossible to obtain data for training of damaged existing structures. That causes importance of development of the method, which diagnoses damage just from data of the intact state structure for existing structures. Therefore we purpose new statistical diagnostic method for structural damage detection. In the present method, system identification using a response surface is performed and damage is diagnosed by testing the change of this identified system by statistical test. The new method requires data of non-damaged state and does not require the complicated modeling and data of damaged state structure. As an example, the present study deals damage diagnosis of a jet-fan which installed to a tunnel on an expressway as a ventilator fan. Damages are detected from load of turnbuckles. As a result, the damage is successfully diagnosed with the method.
Monitoring of delamination is indispensable for CFRP structures. It is, however, very difficult to detect a delamination visually. This demands a new structural health monitoring method. For aerospace structures, it is required to monitor a delamination before flight, and this means the monitoring system must detect the delamination without loading. In authors' previous studies, the delamination can be monitored with the electric resistance change method. The method provided excellent performance of estimations. The method, however, requires complicated electric circuits and uses a two-probe method: two-prove method includes effects of the electric resistance change at the electrodes. To resolve these problems, an electrical potential method is employed here. In the previous paper, the electrical potential method showed poor performance of estimations for delamination cracks located near the center of the specimen. The practical zigzag crack has large effect on the performance of estimation when the delamination locates at the center segment of the specimen. This problem is overcome by means of a two-stage monitoring method. The new method shows excellent performance of estimations on the basis of FEM analyses. In this paper, experiments are conducted to identify the delamination using this method. The applicability of this method is examined using the experimental data.
Delamination is a significant defect of laminated composites. The present study employs an electrical resistance change method in an attempt to identify internal delaminations experimentally. The method adopts reinforcing carbon fibers as sensors. In our previous paper, an actual delamination crack in a Carbon Fiber Reinforced Plastics (CFRP) laminate was experimentally identified with artificial neural networks (ANN) or response surfaces created from a large number of experiments. The experimental results were used for learning of the ANN or regression of the response surfaces. For the actual application of the method, it is indispensable to reduce the number of experiments to suppress the total experimental cost. In the present study, therefore, FEM analyses are employed to make sets of data for learning of the ANN. First, electrical conductivity of the CFRP laminate is identified by means of the least estimation error method. After that, the results of FEM analyses are used for learning of the ANN. The method is applied to actual delamination monitoring of CFRP beams. As a result, the method successfully monitored the delamination location and size only with ten experiments.
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