Introduction to X-Ray Imaging for Industrial Applications
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Transcript of Introduction to X-Ray Imaging for Industrial Applications
Introduction to X-ray imaging for
industrial applications
Markus Tarin President & CEO
MoviMED
Agenda
Agenda
• What exactly are “X-rays” ?
• The X-ray tube
• Typical applications
• Methods of detection
• Detector types
• Challenges in x-ray imaging
• Detector selection
• Example application
• Conclusion
• Q & A
Head x-ray – “Homer Simpson”
The Electromagnetic Spectrum
Historical Background
• German Physicist
• Discovered x-rays or “Roentgen rays” on Nov 8, 1895
• During experimentation with vacuum tubes he noticed a faint glow (fluorescent) on a cardboard covered with “Barium Platinocyanide”
• Named the radiation “x-rays” as in “unknown” rays
• Wilhelm Roentgen received the Nobel Prize in 1901 for this discovery
Wilhelm Conrad Röntgen
*03/27/1845 † 02/10/1923
First X-ray image
• First X-ray images taken
by Wilhelm Roentgen
• 22nd December, 1895
• Shows the hand of
Wilhelm’s wife with ring
The X-ray tube
X-rays
Cathode
Filament
Glass body
Anode with Tungsten target
Electron beam kV
(keV)
The filament provides an
“electron cloud” which is
accelerated by the high
voltage potential
between the anode and
cathode.
The electrons collide and rapidly decelerate on the
high-density Tungsten anode. The energy decay
causes a photon emission. The emitted wavelength is in
relation to the energy loss of the electron.
X-ray Energy
Definition of X-ray energy:
The term xxx kV (kilo Volt or 1 x 1,000 Volt) refers to the high voltage supplied to
the x-ray tube. With other words the potential between the anode and cathode. A higher “kV” setting results in a higher x-ray energy output and a shorter wavelength.
The current (mA – milli-Ampere - 1/1000 A) is the selected current allowed to flow through the filament of the x-ray tube at the selected voltage. A higher current causes a higher x-ray flux.
The term “eV” or more commonly “keV” or “MeV” is the “electron Volt” or the energy given to an electron by accelerating it through 1 Volt. When considering x-rays, the keV or MeV is referring to the output energy of the x-ray photons generated by the x-ray tube.
Examples of Energy (eV)
The following are examples of eV energies:
• Visible light photons: 1.5 – 3.5 eV
• Approximate energy of an electron striking a color
television screen (CRT tube): 20,000 eV (20 keV)
• High energy medical, diagnostic x-ray: 200 keV
• 100W light bulb burning for one hour: 2.2 Trillion
TeV !!! (2.2 Trillion Trillion eV)
• Kinetic energy of an 1,900lb race car traveling at
230 mph: 28 x 10^24 eV
Typical Applications
• Airport/Homeland Security
• Electronics
• General Inspection
• Petro-Chemical
• Automotive
• Aerospace
• Non-Destructive Testing
• Medical/Diagnostic Imaging
• X-ray Fluoroscopy
X-ray detection methods
• Image Intensifier
• Scintillator (Gamma detector)
• Amorphous Silicon
Panel
• X-ray film
• Phosphor plate
scanner (CR)
• others
X-ray image intensifier
Image Intensifier
• Commonly found
in industrial x-ray
applications
• Converts x-rays
into photons using
phosphor
Scintillator
• User for gamma ray detection
• Could be coupled to a photon multiplier counter
• Uses inorganic material to convert gamma rays into photons in the visible waveband
Conceptual overview – Scintillator with detector
Amorphous Silicon Panel
• Energy range from
10 to 160 keV
• Resolution about 48
µm (~10lp/mm)
• Standard frame
grabber interface
• Easy to integrate
• “X-ray camera”
• Compact form factor
Challenges in X-ray imaging
• X-ray applications are generally “light starved”
• Signal to noise ratio is usually not very favorable
• Achieving acceptable image quality requires
careful selection of optics and camera
• X-ray imaging requires a considerable amount of
“domain knowledge”
• Image contrast depends on many factors (x-ray
energy, absorption bands in specimen, type of
materials, focus quality of x-ray beam, selection of
detector, lens and imaging sensor)
• Feature definition may be “fuzzy” or “faint”
Importance of Detector Selection
Why using a standard machine vision
camera for X-ray will not work…
• The light output produced by an image
intensifier is typically very low
• Increasing the x-ray energy to achieve
more light output will not necessarily
improve the contrast ratio
• Using a small pixel size sensor (<7.4um
with 8-bit ADC) results in a limited dynamic
range
• Light starved x-ray imaging competes with
detector noise of the camera
Importance of Dynamic Range
Sensor A Sensor B
Pixel Size 7.4um x 7.4um 16um x 16um
Full well capacity 20,000 e 150,000 e
Read noise 16 e 15 e
Dynamic Range 20,000e/16e = 1,250 150,000e/15e = 10,000
Dynamic Range 62 dB 80 dB
Gray levels ADC @ 10-bit - 1024 ADC @ 14-bit = 16,384
(Effective #of bits: 13.3)
• Sensor B has a dynamic range 8 x higher than sensor A
• X-ray images need to be processed in 16-bit format
Lens Selection
• Due to the large pixel size
requirement, the sensor size of a
camera is also large.
• F-mount lenses are often required
• The field of view and working
distance needs to be matched to
the output port of the image
intensifier
• The lens needs a large aperture
(low f#) to capture all available
light. Ideally f# < 1.0
Example application - BGA
Ball grid array inspection • Higher density integrated circuits also come
with a higher pin count
• The “BGA” or ball grid array IC package type
has little balls as connection leads
• The connections are underneath the chip
and are no longer visible, after assembly
• The solder paste is being placed onto the
circuit board, prior to chip placement
• The chip is then placed onto the PCB and
run through a reflow oven, where the solder
paste melts and forms an electric connection
between the PCB and the ball contacts
• X-ray inspection is the only method to “see
through the circuit board and verify that all
balls are in contact and that there are no
accidental short circuits
BGA – X-ray image
• The solder paste is very opaque
to the x-rays and provides a
very favorable contrast ratio.
• The electronics industry
frequently uses radio isotopes,
emitting gamma rays (MeV
energy)
• Automatic detection algorithms
can be used in this example for
verification.
Image Processing – X-ray
Step 1: Raw x-ray image
BGA – Threshold
Step 2: Threshold type “Moments”
Creates a binary image. Only black
areas are being considered.
BGA - Dilate
Step 2: Dilate
Dilates binary pixels in the object
BGA - Close
Step 3: Close
Closes holes in the blobs
BGA – Particle analysis
Step 4: Particle analysis
Counts objects, measures size and
location. 144 pins found – pass!
BGA defect
• This images show multiple
defects after the soldering
operation of a BGA IC.
• Multiple BGA contacts are
accidentally soldering
together.
• The bridged pins or ball
contacts are creating a
shortcut
• The circuit will not function
properly
BGA defect – raw image
BGA defect - Threshold
BGA defect - Erode
BGA defect – Remove particles
BGA defect - result
• The final image
processing step
reveals 7 shorts
• The blobs are
much larger than
the acceptance
criteria
• Their center of
gravity does not
coincide with the
IC package
definition
Conclusion
• X-ray imaging is a very useful, non-visible imaging tool
• A considerable amount of domain knowledge is required to successfully apply this technology
• Budgetary estimate for X-ray imaging systems range from $60k to $500k and up.
• Exposure to x-ray radiation is potentially dangerous to ones health and safety.
• Automated image processing may not always be possible, due to sometime poor defect definition
• 16-bit image processing is necessary, due to the need for large dynamic range.
Markus Tarin President & CEO
MoviMED
15540 Rockfield Blvd., Suite C110
Irvine, CA 92618
USA
Phone: 949-699-6600
email: [email protected]
www.movimed.com
Q & A