Increasing the Sensitivity of Ultrasonic Phased Array

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.

http://creativecommons.org/licenses/by/3.0/

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


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


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


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


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)


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)


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


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


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


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


Axle without arteficial flaws, overlay of TD-scans for angles 28° - 72°

Signal Processing on Test Wheel Set


Axle with arteficial flaws, overlay of TD-scans for angles 28° - 72°

Examination Result on Axle with Arteficial Flaws


front

top

back

bottom

0

90

180

270

360

Grad

0

90

180

270

360

Grad

front

bottom

top

back

Conclusion - Improvements


• 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?


• 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

Documents

Increasing the Sensitivity of Ultrasonic Phased Array