DC potential difference method are simple and fast non destructive testing method. It measures voltage between two points on surface touched by each needle. In some kind of engineering structural member, neighborhood of iron surface is required to have higher hardness than normal iron ’s one. To meet this demand, quench hardening process is a popular process to make iron hard from surface and hardening depth is important parameter to be ensured in target member after process. Because quench iron increases its resistance by 20 %, D.C.potential method is able to be used for evaluating hardening depth. However output voltage was insensitive for change of deep hardening depth over 5.0mm, measurement would fail over 2.0 mm with improper needle array probe in reality. We developed a novel methodology to determine needle position to improve its applicability over 5.0 mm depth which is demanded in some member. In this methodology, needle position are optimized for cost function that is voltage gradient to hardening depth. Throughout this optimization, (1) an analytical expression of surface voltage which are obtained solve Laplace equation in three dimensional space. (2) CAS system (Maple / MAXIMA) . are invoked. Experimental data shows good coincidence to those numerical computation, and monotone increasing property of voltage to depth are kept up to 10 mm hardening depth. Proposed needle positions have made DC potential difference method possible to evaluate hardening depth over 5.0 mm. The algorithm is most likely to work well with only one response function for this type probe.
Authors had developed an image reconstruction algorithm that can accurately reconstruct images of flaws from
data obtained using conventional ECT sensors few years ago. The developed reconstruction algorithm is designed
for data which is assumed to be obtained with spatial uniform magnetic field on the target surface. On the other
hand, the conventional ECT sensor author used is designed in such a manner that when the magnetic field is
imposed on the target surface, the strength of the magnetic field is maximized. This violation of the assumption
ruins the algorithm simplicity because it needs to employ complemental response functions called"LSF"for long
line flaw which is not along original algorithm design.In order to obtain an experimental result which proves the
validity of original algorithm with only one response function, the authors have developed a prototype sensor for
magnetic flux leakage testing that satisfy the requirement of original algorithm last year. The developed sensor
comprises a GMR magnetic field sensor to detect a static magnetic field and two magnets adjacent to the GMR
sensor to magnetize the target specimen. However, obtained data had insufficient accuracy due to weakness of
the strength of the magnet. Therefore author redesigned it with much stronger magnet this year. Obtained data
with this new sensor shows that the algorithm is most likely to work well with only one response function for
this type probe.
Carbon fiber reinforced plastics (CFRP) composite material, which is expected to reduce the weight of automotive,
airplane and etc., was cut by laser irradiation with a pulsed-CO2 laser (TRUMPF TFL5000; P=800W, 20kHz, τ=8μs,
λ=10.6μm, V=1m/min) and single-mode fiber lasers (IPG YLR-300-SM; P=300W, λ=1.07μm, V=1m/min)(IPG YLR-
2000-SM; P=2kW, λ=1.07μm, V=7m/min). To detect thermal damage at the laser cutting of CFRP materials consisting
of thermoset resin matrix and PAN or PITCH-based carbon fiber, the cut quality was observed by X-ray CT. The effect
of laser cutting process on the mechanical strength for CFRP tested at the tensile test. Acoustic emission (AE)
monitoring, high-speed camera and scanning electron microscopy were used for the failure process analysis. AE signals
and fractographic features characteristic of each laser-cut CFRP were identified.
Over the past few years, the authors have developed a reconstruction algorithm that can accurately reconstruct
images of flaws from data obtained using conventional ECT sensors. The algorithm is simple and fast and
involves few steps, thus making it suitable for implementation on a PC. The algorithm can be applied to study
eddy current systems; it can also be used in conjunction with non-destructive testing methods involving a
magnetic field. However, there is one inherent limitation related to sensor design. In eddy current or magnetic
flux leakage, a conventional sensor is used to detect flaws in damaged areas. This sensor is designed in such
a manner that when the magnetic field is imposed on the target surface, the strength of the magnetic field is
maximized. This measurement method has remained unchanged since the introduction of the technique. The
developed reconstruction algorithm is designed for data obtained by imposing a uniform magnetic field on the
target surface. Recent developments in computer technology have enabled the integration of computing and
testing equipment; in this context, the authors believe that a new sensor for use with reconstruction algorithm
will be required. Therefore, the authors have developed a prototype sensor for applications to magnetic flux
leakage. The developed sensor comprises a GMR magnetic field sensor to detect a static magnetic field and two
magnets adjacent to the GMR sensor to magnetize the target specimen. The results of the combined use of the
sensor and the reconstruction algorithm are presented in this paper.
EMAT, which is based on magnetostrictive effects, was employed to detect flaws in a sample with surface oxide scale. Chromium molybdenum steel (SCM415) was annealed at 600C to 900C from two to eight hours and subjected to EMAT to survey its signal properties. Oxide scales has ferromagnetism. The data from these samples were compared to an actually used samples. The EMAT signal derived from the actual sample was found to be too noisy due to Barkhausen effect to identify reflections from internal flaws and to reconstruct flaw images in a computer. This study proposes spectrum analysis and statistical methods based on noise probability to decrease this noise.
A lack of safety and the reliability of the existing metallic structure can threaten people's lives today. It is
getting stronger to demand to ensure reliable safety in society. Non Destructive Testing(NDT) can support to
public safety with finding damaged structure. Eddy Current Testing (ECT) is a one of NDT for metallic or
conductive materials. It already plays an important role in very wide field such as airline and power plants
for maintenance, ironworks for production. Though ECT is considered as a finished testing method,it has the
unwanted property that flaw blur in ECT signal.This defect partly comes from the essential principle of ECT.
In order to obtain fine image of flaw, the authors proposed a method with signal processing to reconstruct more
finer image of flaw from ECT signal. The method is based on simple relationship that signal are expressed as
a convolution of response function and flaw shape. Many obtained results, more fine images of points flaw and
both short and long line flaw than images of those ECT signal were reconstructed, show validity of the method
for those flaws. Nevertheless its aim was fundamental survey on validation of the method so that tested flaws
were limited in shape.In this paper,beyond that limitation, the authors wish to report the results of applications
to complex shape flaws that are likely to be found in actual inspection site. The obtained reconstructed images
show notable results indicate that the validity is kept even for complex flaw.
An eddy current testing (ECT) and an electromagnetic acoustic testing (EMAT) employ electromagnetic methods
to induce an eddy current and to detect flaws on or within a sample without directly contacting it. ECT produces
Lissajous curves, and EMAT gives us a time series of signal data, both of which can be directly displayed on
nondestructive testing (NDT) equipment screens. Since the interpretation of such output is difficult for untrained
persons, images need to be properly reconstructed and visualized. This could be carried out by single-probe
2/3D scanners with imaging capabilities or with array probes, but such equipment is often too large or heavy
for ordinary on-site use. In this study, we introduce a flexible scanning tablet for on-site NDT and imaging of
detected flaws. The flexible scanning tablet consists of a thin film or a paper with a digitally encoded coordinate
system, applicable to flat and curved surfaces, that enables probe positions to be tracked by a specialized optical
reader. We also discuss how ECT and EMAT probe coordinates and measurement data could be simultaneously
derived and used for further image reconstruction and visualization.
Eddy Current Testing(ECT) has been used in wide field such as airline and power plants for maintenance, ironworks for production.
However original flaw shape blur in image by signal of ECT.
In our previous work an image reconstruction method from signal had been proposed.
The method is based on
that simple relationship between signal and source are described by a convolution of response function and flaw shape.
The method was able to show more fine image of points flaw, short line flaw, long line flaw
than images of those original signal.
One difficulty in the method was to determine empirical parameter by trial and error.
In this paper, we propose a concept of modified response function and signal that
enable to make empirical parameter unnecessary.
Those modification process is fully programmable and is carried out automatically.
Validity of introducing those modification are considered from mathematical view point.
Numerical results shows the method with this concept
reconstructed image as same as empirical parameter method.
An image by Eddy Current Testing(ECT) is a blurred image to original flaw shape. In order to reconstruct fine
flaw image, a new image reconstruction method has been proposed. This method is based on an assumption that
a very simple relationship between measured data and source were described by a convolution of response function
and flaw shape. This assumption leads to a simple inverse analysis method with deconvolution.In this method,
Point Spread Function (PSF) and Line Spread Function(LSF) play a key role in deconvolution processing. This
study proposes a simple data processing to determine PSF and LSF from ECT data of machined hole and line
flaw. In order to verify its validity, ECT data for SUS316 plate(200x200x10mm) with artificial machined hole
and notch flaw had been acquired by differential coil type sensors(produced by ZETEC Inc). Those data were
analyzed by the proposed method. The proposed method restored sharp discrete multiple hole image from
interfered data by multiple holes. Also the estimated width of line flaw has been much improved compared with
original experimental data. Although proposed inverse analysis strategy is simple and easy to implement, its
validity to holes and line flaw have been shown by many results that much finer image than original image have
Martensitic transformation and degradation characteristics for Fe-Pd ferromagnetic shape memory alloy were investigated by the developed AFM (Atomic Force Microscope)/MFM (Magnetic Force Microscope) hybrid nano-characterization technique. In AFM martensitic transformation was detected by the changes of surface topography of martensite plates. In MFM martensitic transformation was detected by the changes of magnetic domain structures. This technique has an advantage that martensitic transformation characteristics such as martensitic transformation temperature and reverse transformation temperature can be measured at microscopic and nanoscopic small area. Degradation characteristics of martensitic transformation under cyclic loading were also detected by the changes of AFM and MFM images. In AFM images surface topography of martensite plates became flat and in MFM images the morphology of magnetic domain structures became unfocused under cyclic loading. Then it was found that the hybrid nano-characterization was very high sensitive technique to evaluate degradation for Fe-Pd ferromagnetic shape memory alloy.