increasing the sensitivity of ultrasonic phased array
TRANSCRIPT
ESIS TC24 Workshop: Integrity of Railway Structures
1 License: http://creativecommons.org/licenses/by/3.0/
Increasing the Sensitivity of Ultrasonic Phased Array Wheel Set Axle Inspection by
Using Signal Processing
Thomas HECKEL 1, Rainer BOEHM 1, Wolfgang SPRUCH 2, Sebastian JACOB 2 1 Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany
2 Büro für Technische Diagnostik GmbH & Co. KG BTD, Brandenburg, Germany
Contact e-mail: [email protected]
Abstract
The geometry and the surface condition of the shaft influence the signal to noise ratio of ultrasonic inspection of wheel set axles significantly. Signal processing algorithms may be applied on the recorded data of in-service inspections to decrease sensitivity to geometry changes by minimizing echos generated by indications of the seats. Using signal processing methods also enable the reduction of the influence of the individual condition of the wheel set on the sensitivity of the inspection. The main challenges to overcome by signal processing are on the one hand difficult coupling conditions of the probes attached to the outer surface of the axle due to the complex geometries of the shaft. On the other hand coupling quality can be decreased by a mixture of dust, mud and grease on the shafts. Therefore signal processing algorithms applied have to be stable against deviations in geometry and as well have to compensate variations in signal amplitude caused by altering coupling conditions. Different off-line algorithms have been developed and tested against each other on a given number of measured data sets by BAM and BTD at laboratory scale. Solutions for use in the field will be presented.
INCREASING THE SENSITIVITY OF ULTRASONIC PHASED ARRAY WHEEL SET AXLE INSPECTION BY USING SIGNAL PROCESSING
25.09.2017 ESIS TC-24 Wittenberge 2017, Talk 1.4 1
Thomas Heckel1, Rainer Boehm1, Wolfgang Spruch2, Sebastian Jacob2
1 BAM Bundesanstalt für Materialforschung und –prüfung, Berlin, Germany2 BTD Büro für Technische Diagnostik, Brandenburg, Germany
25.09.2017
ESIS TC24 Wittenberge 2017, Talk 1.4
In-Service Inspection of Wheelsets
2
Boogie SBB EC Waggon SBB Cargo Wheelset
Bilder:Copyrighted free use, Files moved from de.wikipedia, Kategorie:Datei:Mit OTRS-Freigabe to Commons
25.09.2017 ESIS TC-24 Wittenberge 2017, Talk 1.4
In-Service Inspection Using Angle Beam Probes
325.09.2017 ESIS TC-24 Wittenberge 2017, Talk 1.4
Pk
seat for brake disc I
Pk
25.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4 4
- Change coupling conditions to local immersion testing- sensor size increased to gain sensititvity- use of an acoustical lens to optimize soundfield- angular scan area extended
Optimization of probe design
Change Coupling Conditions to Local Immersion Testing Technique
525.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
local „immersion technique“
RStahl
Plexiglas
RStahlWasser
Plexiglas
steel
plexiglas
watersteelsteel
plexiglas
Increase of Sensor Size to Gain Sensititvity
625.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
The increase of the sensor area leads to defocussing of the sound beam on curved surfaces.
echo heightfor point type reflector
steel
plexiglas
steel
plexiglas water
Rsteell
plexiglas
Rsteel
water plexiglas
Use of an Acoustical Lens to OptimizeSoundfield
725.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
echo heightfor point type reflector
compensation of defocussing by use of acoustical lens
steel
steel
water
plexiglas
R‘
Bm
R0
a0
s‘
a
steel
lensplexiglas
R‘ R0
water
Rsteel
plexiglas
Acoustical Lens – Performance Test
825.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
Gain of sensitivity by acoustical lenson a 2 mm saw cut is +6 dB to +12 dB
22
28
34
40
46
52
58
64
70
25 30 35 40 45 50 55 60 65
Vers
tärk
ung
in d
B
Einschallwinkel in °
ohne mit Wasserlinse
Probe in immersion setupwith a waterpath of 2 mm
Extend of Angular Scanning Area
925.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
16 elements, width of element 1.4 mm 32 elements, width of element 0.9 mm
-3dB
-6dB
-12dB-3dB
-6dB
-12dB
25.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4 10
Optimization of scans/images for evaluation
- suppression of echos induced by geometry- suppression of noise- separation of spurious signals
Signal Processing
Signal ProcessingSuppression of Echos Induced by Geometry (1)
1125.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
Probe: 3 MHz, 16 elementsα0 = 45°, α = 10° - 70°
Re6
120
146
191
170
191
161
330
Reflektor 6
TD - Scan
Selected A-scan
used for
reference
TD-Bild original Subtracted TD-Scan
rota
tion
soundpath
A - Scan
Signal ProcessingSuppression of Echos Induced by Geometry (2)
1225.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
TD - scan
A - scan
Identification ofcircumferentialindications by meansof statistic methodsand image processing
Calculation of TGC curves to reducecircumferentialindications
rota
tion
soundpath
Signal ProcessingThe New Approach
1325.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
Axle with arteficial flaws, software by BTD, overlay of TD-scans for angles 28° - 72°
Filteringwithout
modification ofecho height
GOAL:
display of relevant indications only
SOLUTION:suppression of
unwanted „noise“
position on axis
rota
tion
Signal ProcessingNo Modification in Amplitude is Allowed
25.09.2017 14
Quelle: DB
Quelle: BMVI
raw data decisionmatrix
processedimage
statistic based signal processing
ESIS TC24 Wittenberge 2017, Talk 1.4
classification
Signal ProcessingStatistical Evaluation of Raw Data Set
1525.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
0.5
1
1.5
2
2.5
0 10 20 30 40 50 60 70 80 90 100
Au
swa
hlg
röß
e A
W
Anteil der A-Bilder mit Echosignal in %
Formanzeigenverdacht bei AW < 1
Indication by flaw?
Indication by geometry0
0.5
1
1.5
2
2.5
3
3.5
4
0 10 20 30 40 50 60 70 80 90 100
Au
swa
hlg
röß
e A
W 2
Umfangsposition
Fehleranzeigenverdacht bei AW2 > SNRmin
Indication
Criterion AW1: AW1 < 1Recognition of geometry causedcircumferential indications
Criterion AW2: AW2 > SNRmin
Recognition of indication caused by flaws
Distinguish between noise, flaws andspourious signals on form and amplitude
Rotation of axle in %Number of A-Scans with significant signal in %
Cri
teri
onAW
1
Cri
teri
onAW
2
Signal ProcessingStatistic Evaluation on Test Data Set
1625.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
echo
hei
ght
echo
hei
ght
echo
hei
ght
Based on the raw data set the algorithm computes a decision matrix.
raw data set decision matrix processed data set
Where relevant information has been detected, the information from the raw data is copied to theprocessed data set.
Signal Processing on Test Wheel SetSignificant Decrease of Noise
1725.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
Axle without arteficial flaws, overlay of TD-scans for angles 28° - 72°
Signal Processing on Test Wheel Set
1825.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
Axle with arteficial flaws, overlay of TD-scans for angles 28° - 72°
Examination Result on Axle with Arteficial Flaws
1925.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
front
top
back
bottom
0
90
180
270
360
Grad
0
90
180
270
360
Grad
front
bottom
top
back
Conclusion - Improvements
2025.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
• Local immersion technique
• Increase of sensitivity by use of lager transducer
• Optimization of sound field by use of a lens
• Increase in scan area by use of smaller elemtens
• Identification and suppression of geometry caused indications
• Suppression of noise
• Suppression of spourios signals
Fachbereich 8.4
Conclusion – What is left to do?
2125.09.2017 ESIS TC24 Wittenberge 2017, Talk 1.4
• Test algorithms in the field
• collect data sets from different types of axles
• Make thresholds adaptive to signal quality
Fachbereich 8.4
Gefördert vom
im Rahmen eines MNPQ – ProjektsMessen, Normen, Prüfen,Qualitätssicherung