EWGAE 2010 Vienna, 8th to 10th September

Fatigue Testing of Ship Building Material with Acoustic Emission

Ireneusz BARAN, Marek NOWAK, Jerzy SCHMIDT Cracow University of Technology, Laboratory of Applied Research, 31-864 Krakow, Poland

Keywords: Fatigue test, crack propagation, AE monitoring, transport products

Abstract

Corrosion damages and fatigue cracks are the main causes of structural failures in all surface transport products like ships, road tankers and railway tank cars. Both types of degradation, i.e. the degradation of material and structure, are the subject of investigations carried out within the framework of a collaborative project of the 7th Framework Programme (Transport) entitled “Cost effective corrosion and fatigue monitoring for transport products”.

In this paper, the first fatigue tests using acoustic emission (AE) performed on ship building materials have been demonstrated. AE enables us to monitor the crack propagation during low fatigue tests performed on specimens under asymmetric three-point bending loading. It was expected that fracture behaviour would move from Mode I to Mixed-Modes I/II, which would be closer to reality. For reference, tests were also made in liquid to obtain and evaluate the differences in AE signal propagation in liquid and in material directly contacting this liquid. The data obtained during fatigue tests will be included in a database used in pattern recognition analysis to separate the signals due to fatigue crack propagation and corrosion damages from background noise. Introduction

Structural failures not detected on time and not monitored in time are potentially the reasons of catastrophic accidents with tremendous pollution of the maritime environment or fatal explosions during the use of transports vehicles. The preventive maintenance activities are usually carried out on time drive basis, to detect and identify the evolving defects in time and enable appropriate repairs. As an example may serve transport products for cargos like crude oil and pressurised gases, which have to be taken out of service for visual inspection and subsequent non-destructive tests (NDT). Despite this high effort, the risk of not detecting the onset of a defect is still implied in this maintenance process and thus failure within the next service period may occur.

Based on these facts, a consortium consisting of different research centres, universities and industrial companies from the following countries: Austria (as coordinator TÜV Austria Services GmbH), Estonia, Germany, Great Britain, Greece, Poland, Portugal and Romania was created and started in 2008 an EC founded collaborative project of the 7-th Framework Programme (Transport) entitled: “Cost effective corrosion and fatigue monitoring for transport products”.

The intention of this project is to develop a discontinuous spot testing and permanent installed system. The aim of both systems is to detect the corrosion attack and fatigue cracks that occur in a structural material used for transport products. The proposed maintenance process is based on monitoring the status of the structural integrity in terms of developing fatigue cracks and active corrosion using the Acoustic Emission (AE) technology. It has been proved that AE detects active cracks as well as active corrosion as confirmed by the results of EU-funded project "Corrosion detection of ships (EVG1-CT-2002-00067)". By the application of AE sensors installed permanently on pre-determined hot spots of ships, tank cars and road tankers, the conventional maintenance and inspection can be replaced by a cost-effective and condition-based detection of defects and their follow-up in time.

This paper describes a part of investigations done within the project, related with the AE-

based laboratory fatigue tests performed on a ship building material by the Laboratory of Applied Research at Cracow University of Technology (Poland). Laboratory fatigue testing

The high-strength steel, type GL-A32 (material 1.0513, LR AH32), for ship hull construction (delivered as plates 10 mm thick) was chosen for fatigue bend specimens. The mechanical properties of the material tested in laboratory on specimens cut-out from the delivered plates were the following: tensile yield strength 300MPa, ultimate tensile strength UTS 440MPa, elongation 50%, bending yield strength 440MPa and ultimate bending strength UBS ≥550MPa.

The general assumptions for laboratory fatigue testing with AE were the following: • the specimens would be large elements made from the steel plate used by repair yard in

shipbuilding, • the specimens would be welded using the same welding technology that is used by the

repair yard, • the scheme of loading should allow for changes in the notch sensitivity zone and moving

from Mode I to Mixed-Modes I/II, • the frequency of loading during measurements with AE would be in the range of 0,2÷1,0Hz,

according to project definition based on real work conditions of such structures, • the fatigue tests would be performed with sensors mounted on the plate and additionally

with sensors immersed in liquid, • the liquid would be in direct contact with the propagating crack to check the differences in

AE signals when travelling through the liquid and through the solid material.

Based on literature studies, FEM simulation and the subsequent preliminary tests performed on large specimens, for further studies the asymmetric three-point bending test was chosen as a loading scheme.

The dimensions of the specimens, the position of the weld and of the flaw-initiating notch as well as the layout of supports are shown in Fig.1.

The first stage covered preliminary tests, which mainly aimed at a verification of the adopted scheme of loading. Figure 2 shows the direction of crack development and propagation as obtained by FEM simulation for the adopted scheme of loading.

Fig.1. The size of fatigue specimens and layout of supports for three-point bending loading

thickness 10mm

weld

supports

semi-elliptical

surface flaw

Fig.2. Crack propagation direction based on FEM simulation

for the adopted scheme of loading

The fatigue tests conducted according to the adopted asymmetric three-point bending loading scheme confirmed the validity of the assumptions of fracture behaviour and enabled moving from Mode I to Mixed- Modes I/II. Figure 3 shows specimen fracture and cross-section with fatigue crack propagating after preliminary tests.

Fig.3. The results of preliminary fatigue tests – specimen fracture and cross-section with well

visible fatigue crack propagation and weld The next step included proper fatigue tests using AE. The acoustic emission was measured by

AMSY 5 system with ASIP 2 dual channel AE board made by Vallen Systeme GmbH. Two types of sensors, i.e. VS75-V and VS150-RIC, were used, as well as AEP4 preamplifiers with 34dB gain. A schematic layout of the sensors is shown in Fig. 4.

For initiation of fatigue crack, a hydropuls dynamic testing machine type IST Systems PL400 was used. In this case, the loading frequency was in the range of up to 5 Hz. On the other hand, during fatigue tests with AE, the electromechanical machine with strengthened loading system type Zwick Z100 was used, and then the loading frequency was 0,4 Hz. The hydropuls dynamic testing system has generated too high level of noise during tests with AE monitoring but the electromechanical static system has generated very low and acceptable level of noise.

Figure 5 shows fragment of a typical run of the fatigue loading curve in asymmetric three-point bending test and an amplitude of recorded AE signals, while Figure 6 shows fatigue crack propagating in one of the examined specimen.

Fig.4. Schematic layout of AE sensors with supports on fatigue specimens – AE signals are

travelling through the specimen material (metal) only

Fig.5. Fatigue loading and amplitude of recorded AE signals

Fig.6. A view of open crack and the direction of its propagation during fatigue tests

At this stage of research, the AE sensors were mounted only on the specimen material (the

plate) tested according to the scheme shown in Fig. 4. The next stage included fatigue tests performed with AE measurements and sensors immersed

in liquid (only VS75-V), which was in direct contact with the tested material and with the

propagating fatigue crack. Schematic layout of AE sensors is shown in Figure 7, while Figure 6 shows fatigue crack propagating in one of the examined specimen.

Fig.7. Schematic layout of AE sensors (VS75-V and VS150-RIC) with supports on fatigue

specimens and AE sensors immersed in liquid (only VS75-V) – AE signals are travelling through both specimen material (metal) and liquid

Fig.8. A view of open crack and the direction of its propagation

during fatigue tests with liquid Analysis and results

The obtained measurement data were subjected to analysis and prepared for further numerical processing, where „pattern recognition” technique would be used to separate the AE signals originating from the propagating fatigue crack and corrosion damage from acoustic background noise.

Measurement data were analysed, based on tests during which the AE sensors were mounted only on the examined specimens (the AE signals were travelling only through the tested material, i.e. metal). The AE measurements during fatigue tests enabled detection and location of fatigue cracks and monitoring their development in successive fatigue loading cycles. Figure 9 shows the location of AE sources for VS75-V (a) and VS150-RIC (b) sensors. Peaks (3D) and squares coloured in red and blue (2D) mark tips of the propagating fatigue crack.

a)

b) Fig.9. Location of AE sources for VS75-V (a) and VS150-RIC (b) sensors during fatigue test (2D and 3D view) – AE signals are travelling only through the specimen material (metal)

The analysis was next carried out on the measurement data collected during tests carried out

with AE sensors installed directly on the examined specimens and also immersed in liquid (VS75-V). In this case, the AE signals were travelling through both specimen material (metal) and liquid, which was in direct contact with the specimen material and with the developing fatigue crack. The AE measurements during fatigue tests enabled detection and location of fatigue cracks as well as monitoring their development in successive fatigue loading cycles for AE signals propagating in both the specimen material and liquid. Figure 10 shows location of AE sources for VS75-V sensors. Peaks (3D) and squares coloured in red and blue (2D) mark tips of the propagating fatigue crack

Fig.10. Location of AE sources for VS75-V sensors during fatigue test with AE sensors

immersed in liquid (2D and 3D view) – AE signals are travelling through both specimen material (metal) and liquid

The figures 11, 12 and 13 present example of results of the analyse of the AE recorded signals

generated by the constantly developing fatigue crack during above 2500 loading cycles. Thus, figure 11 shows location of AE clustered sources along crack and level of load (with first Hit amplitude) at which every event was generated for determined cycle loading number. The PCTA parameter in graphs is the number of cycle loading. Figure 12 is result of filtering of location from fig.11 and presented location of AE source in selected cluster zone and level of load (with

first Hit amplitude) at which every event was generated for determined cycle loading number. Figure 13 show example of results of pattern recognition analysis in Visual Class application on AE signals for sources in fig.12. Unsupervised learning on single file was used (AE signals from clustered sources). It can be observed that dots create lines or clouds of concentrated dots (figs. 11, 12 and 13) from events for AE source and which Visual Class associate as similar types of waveforms into individual classes.

a)

b) Fig.11. Location of AE sources for VS150-RIC (a) and VS75-V (b) sensors during fatigue

test and corresponding to them level of load with amplitudes of events in graph Load vs. PCTA (number of cycle loading)

a)

b) Fig.12. Location of AE source in selected cluster zone for VS150-RIC (a) and VS75-V (b) sensors during fatigue test and corresponding to them level of load with amplitudes of

events in graph Load vs. PCTA (number of cycle loading)

a) b) Fig.13. Example of Visual Class analysis of AE signals recorded by VS150-RIC (a) and

VS75-V (b) (sensors mounted on the plates & immersed in liquid) for source in selected cluster zone during fatigue test – used unsupervised learning on single file

Figure 14 shows ultimate result of fatigue tests on the specimen after several hundred

thousand loading cycles – the size of crack exceed the critical value for loading conditions and the tested specimen lost the stability.

a)

b)

Fig.14. A view of open crack after fatigue tests (a) with liquid and the specimen fracture as cross-section along the fatigue crack (b) with well visible fatigue crack propagation

Conclusions

Based on the obtained results and on their analysis, the following conclusions can be drawn: • AE measurements during fatigue tests series have shown, that it is possible to acquire AE

originated by fatigue cracks with sensors directly mounted at test specimens. • AE waves coming from the fatigue crack and propagating through the liquid directly to

the AE sensor can be received by the immersed sensors. • The acquired AE data (AE parameters and transient time signals) were evaluated, and the

following step will be use a pattern-recognition analysis software to identify the recorded AE signals.

• For the monitoring of the structural condition of a testing object and later evaluation of possible defects, it is necessary to be able to distinguish between wanted (real) AE signals and the so called background noise.

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