The paper is the result of a 2 years research made in collaboration with Aerospace company Leonardo.
The object was to evaluate the behavior of different type of composite with carbon fiber and glass fiber.
The samples were tested on a three point bending and monitoring continuously during the application of load and full test up to the failure.
Characteristic of the test was to maintain constant the load and verify after two and three days if really no fractures happen.
Only in these conditions the load will slowly increased and again time over.
The research has taken to the following conclusions: there is a load (Delay Cracking Load) at which a slowly cracking phenomena start also maintaining constant the load.
The importance of the research was that only through acoustic emission is possible to determine for each type of composite the DCL (Delay Cracking Load).

Measurement-Based Model of Structural Sound Transmission in a Concrete Specimen

In the field of Non-Destructive Testing and Structural Health Monitoring the propagation of sound in solids is used in methods like acoustic emission, ultrasonic testing and vibration based approaches. The acoustic path in the material has a major influence on the measured sensor signal and therefore has to be taken into account. Important parameters are the position of the source and the sensor. From the signal processing point of view the behaviour of the acoustic channel can be described by position dependent transfer functions. A typical way to predict such functions is by simulation which requires a lot of prior knowledge like material properties and the shape of the specimen. In this paper a different approach based on real world measurements is presented. The sound transmission in a concrete specimen (dimensions 1451 x 105 x 100 mm) between an actuator and an acceleration sensor was investigated in the frequency domain of 200 to 9,900 Hz. In total 195 measurements were made alongside the axis of the specimen in a 5mm grid. Based on these measurements a model of the acoustic channel was designed and evaluated which describes the system behaviour in terms of absolute amplitude frequency responses alongside one dimension of the specimen. The response at one frequency bin over the position is modelled by an absolute sine function with an amplitude modulation term. The position based periodicity is modelled assuming only one speed of sound. The parameters of the model were derived by a genetic optimization algorithm. Except for positions very close to the source and close to the end of the specimen, the model predicts the absolute amplitude frequency response alongside the specimen with good accuracy, achieving a normalized mean square error below 0.01 per sample at frequencies with sufficient signal-to-noise ratio.

Early detection of fatigue cracks in truck trailer structures by acoustic emission testing

In fatigue tests, acoustic emission can be measured when cracks occur. In this work the equivalent stresses on a test specimen, modelled after a section of a truck trailer, are calculated using FEA. This information is used to determine the position with the highest probability of a crack occurring. After performing a series of fatigue tests to generate a Wöhler diagram and recording acoustic emissions, an adaptive filter for processing the signal data is presented. In a further experiment, a sample is tested in a fatigue test until acoustic emissions can be detected with the help of the presented signal processing. Further, the resulting crack is examined by preparation of a microsection. Subsequent analysis of the samples strongly indicate that the AE detection algorithms were indeed able to detect microfractures well in advance of the occurrence of failures. In this paper, the accuracy of the detections is discussed by comparing their results with those from the metallographic and microscopic examinations of the tested samples. The use of external variables to validate the detections is also presented, as well as the experimental set-ups and post-processing strategies.

The combined use of millimeter wave imaging and acoustic emission for the damage investigation of glass fiber reinforced polymer composites

Polymer composite materials are used in numerous applications, including automotive and civil engineering. The mechanical behaviour and damage of composites is not as straightforward as that of more conventional materials, like metals. Different damage modes are developed depending on different parameters; material properties, lay-up and loading conditions. However, investigating the damage of composites with respect to all these parameters is of great importance if full characterization of the materials is necessary. Moreover, monitoring the damage of composites under different circumstances in lab conditions can be used as damage predictive tool in real applications and for the establishment of damage criteria. For all above reasons, Non-Destructive Techniques (NDTs) are usually used to monitor the damage of materials. Acoustic Emission (AE) is commonly used to distinguish damage modes of the composites by interpreting the elastic waves that generate in the material when it undergoes irreversible changes. AE is a powerful technique and by using relatively simple equipment, damage can be detected and characterized during loading. However, interpretation of the AE data is not so simple in the case of composites and most of the times it can provide qualitative but not quantitative conclusions. For this reason, in this research AE is combined with Millimeter Wave Imaging, which is an emerging method based on electromagnetic wave radiation within the 30 to 300 GHz band, enabling non-invasive, non-ionizing and non-contact examination of dielectric materials, like Glass Fiber Reinforced Polymers (GFRPs). The Millimeter Wave Imaging technique used in our research combines various advantages in comparison to other NDTs, like high resolution, high defect-detection and positioning capability, owing to its high penetration capability. In this research, the potential of combining the two NDTs, AE and Millimeter Wave Imaging for the damage characterization of GFRP flat specimens under tensile loads is investigated for the first time.

Acoustic Emission application to detect nanoscale fracture on polymers with self-healing ability

One of the most promising technologies of today concerns the inclusion of nanochannels into polymer in order to develop composites with self-healing ability. Nanochannels carry healing agent that aims to fill and repair cracks at micro-scale. The damage processes of nanochannels reinforced polymers is complex and differentiates from pure polymer. In-depth damage assessment remains challenging since there is no testing procedure that permits crack arrest at micro-scale. In practice, the mechanical response of nanochannel polymers is measured applying fatigue regime simulating loading cycles in service life. But the moment that stiffness degradation is detected there is extended macrocracking due to brittle nature of polymers. In other words, stiffness degradation cannot be considered as guide to arrest testing at crack nucleation stage. To overcome this issue, Acoustic Emission technique is applied during fatigue tests in order to monitor early stage damage. Based on acoustic wave features analysis, the test stops as soon as fracture process zone forms and before degradation in stiffness is measured.




The paper deals with the issues of application on the basis of acoustic emission (AE) method of continuous monitoring of hot industrial steam overheating pipelines in operation with prediction of breaking load. Possibilities of introducing AE method for continuous monitoring of pipelines of power unit No1 of Kiev TPP-6 were analyzed. Acoustic properties of steam pipeline material were studied. Preliminary high-temperature AE studies of steam pipeline material were conducted. Mounting and testing of continuous AE monitoring system, its putting into trial operation, and correction of settings on the basis of obtained measurement results were performed. It is shown that breaking load predicted by AE continuous monitoring system is determined with accuracy sufficient for practical purposes. Control schematics and features of system practical application are presented.

Combining acoustic emission with passive thermography to characterize damage progression in cross-ply CFRP laminates during quasi-static tensile loading

Understanding the gradual failure process of carbon fiber reinforced plastics (CFRP) is the key for exploiting their full potential for lightweight applications. Acoustic emission (AE) can support this process through the detection and evaluation of transient acoustic signals released from loaded CFRP specimen in the moment of damage initiation and progression. This way, not only the presence of damage, but also its location, severity and type can be determined by analyzing arrival times as well as energy and frequency contents of the acquired acoustic signals.
In order to differentiate between different types of damage, one has to identify their acoustic signature. This is usually done by correlating extracted AE parameters from acquired signals during a mechanical test with the resulting damage pattern of the specimen that is visualized offline in a time consuming process by imaging methods such as X-ray tomography or microscopy.
In this study, passive thermography is utilized to identify occurring damage inline on the basis of their released heat patterns to support the AE analysis in the identification of acoustic fingerprints and the characterization of damage progression.
Mechanical tests are performed on cross-ply CFRP coupon specimen subjected to quasi-static tensile loading in the 0° and 90° fiber direction while an IR camera and two wide band AE sensors are utilized to monitor the specimen during the test. Heat patterns are extracted from the series of IR data through advanced image processing techniques and correlated with the generated AE signals in order to identify damage modes such as fiber breakage or matrix fracture. An unsupervised pattern recognition approach is then utilized to find similar AE signals and characterize the gradual failure process in the specimen. The outcome is validated with the resulting damage pattern that is visualized offline via X-ray tomography after the mechanical test.

The combined use of magnetoacoustic and magnetic parameters for evaluation of structure and strength of steels subjected to plastic deformation and heat treatment

The influence of excitation and detection conditions on the magnetoacoustic emission (MAE) parameters of ferromagnets of different chemical composition was investigated. It is established that the dependence of the MAE amplitude on the remagnetizing field frequency has nonmonotonic character and that the maximum of the MAE amplitude of all investigated ferromagnet materials corresponds to a field frequency of 3–5 Hz. The decrease of MAE amplitude with following increase of the alternating field frequency caused by the action of eddy currents. It is shown that the value of the field corresponding to the MAE maximum, which for a given time dependence of the remagnetizing field can be determined by the time shift in an oscillogram, can be a new parameter of materials characterisation of ferromagnets.

The magnetic properties of steels of different grades subjected to various thermal treatments have been investigated. It is shown that the residual magnetic induction and induction of coercive return of steels is a sufficiently universal parameters of temperature testing of tempering and annealing of steels. These testing parameters can be used both separately (single-parameter testing) and jointly (two-parameter testing). Presence of correlation between residual magnetic induction and amplitude of magnetoacoustic emission of annealed steels allows to recommend MAE amplitude as a testing parameter in scanning systems of ferromagnetic steels materials characterisation.

Acoustic Emission Response to Fatigue Damage of Additively Produced and Cast Materials

Additive manufacturing (AM) or 3D printing technologies allows to produce parts with complicated shapes in a relatively short time and without big material waste. These parts are more and more used in different types of engineering construction. The latest studies are mainly aimed at improving the quality of the material produced by AM in order to achieve the same or better quality as conventional materials. It brings the need for testing of these materials.
Presented study evaluates and compares the fatigue processes of additively produced and cast materials using acoustic emission method. The used additive technology is the selective laser melting (SLM), which enables to produce metal parts. Tested materials are aluminium alloys AlSi9Cu3 and AlSi10Mg, which are commonly used in aluminium castings production. Both materials are tested in as-cast or as-built condition without any heat treatment. All samples were subjected to fatigue bending tests in high-cycle area and the results were evaluated by acoustic emission measurement. This allows a deep analysis of the fatigue process and compare the characteristics of both materials. The main goal is to analyse the acoustic emission response to fatigue damage and the correlation between this response and fracture mechanism.
Results shows that fatigue life of SLM material is better than casting material with same chemical composition. Acoustic emission detects stages of fatigue process and crack initiation and localization.