“…The here-considered full-scale test was originally part of a wider research program focused on the mechanical characterization and modelling of fretting fatigue damage in railway axles. All the details and results about this research program can be found in 12,13 ,16 .…”
Section: Methodsmentioning
confidence: 99%
“…According to, 1 the central area of this standardized full-scale specimen (i.e. the seat, the T-transitions on both sides and a part of the cylindrical body on both sides) is fully representative, from the point of view of full-scale test results, of real axles in the regions where the wheels are pre-fitted and the adjacent areas.Figure 2.Experimental setup: 13 (a) full scale specimen; (b) position of artificial notches from the edge of the seat; (c) section of artificial notches on press-fit seat; (d) scheme of the Vitry test bench; (e) Vitry test bench parts.…”
Railway axles are safety-critical components of the rolling stock and the consequences of possible in-service failures can have dramatic effects. Although this element is traditionally designed against such failures, the initiation and propagation of service cracks are still occasionally observed, requiring an effective application of non-destructive testing and structural health monitoring approaches. This paper investigates the application of structural health monitoring by acoustic emission to the case of solid railway axles subject to fretting fatigue damage. A full-scale test was performed on a specimen in which artificial notches were suitably manufactured in order to cause the initiation and evolution of fretting fatigue damage up to the stage of relevant propagating fatigue cracks. During the test, both periodical phased array ultrasonic inspections and continuous acquisition of acoustic emission data have been carried out. Moreover, at the end of the test, the specimen was inspected, analyzed and evaluated by visual inspection and magnetic particles testing, while acoustic emission raw data were post-processed by a special unsupervised machine learning algorithm based on an Artificial Neural Network. It is demonstrated that the proposed methodology is very effective to detect the onset of crack initiation in a non-invasive and safe way.
“…The here-considered full-scale test was originally part of a wider research program focused on the mechanical characterization and modelling of fretting fatigue damage in railway axles. All the details and results about this research program can be found in 12,13 ,16 .…”
Section: Methodsmentioning
confidence: 99%
“…According to, 1 the central area of this standardized full-scale specimen (i.e. the seat, the T-transitions on both sides and a part of the cylindrical body on both sides) is fully representative, from the point of view of full-scale test results, of real axles in the regions where the wheels are pre-fitted and the adjacent areas.Figure 2.Experimental setup: 13 (a) full scale specimen; (b) position of artificial notches from the edge of the seat; (c) section of artificial notches on press-fit seat; (d) scheme of the Vitry test bench; (e) Vitry test bench parts.…”
Railway axles are safety-critical components of the rolling stock and the consequences of possible in-service failures can have dramatic effects. Although this element is traditionally designed against such failures, the initiation and propagation of service cracks are still occasionally observed, requiring an effective application of non-destructive testing and structural health monitoring approaches. This paper investigates the application of structural health monitoring by acoustic emission to the case of solid railway axles subject to fretting fatigue damage. A full-scale test was performed on a specimen in which artificial notches were suitably manufactured in order to cause the initiation and evolution of fretting fatigue damage up to the stage of relevant propagating fatigue cracks. During the test, both periodical phased array ultrasonic inspections and continuous acquisition of acoustic emission data have been carried out. Moreover, at the end of the test, the specimen was inspected, analyzed and evaluated by visual inspection and magnetic particles testing, while acoustic emission raw data were post-processed by a special unsupervised machine learning algorithm based on an Artificial Neural Network. It is demonstrated that the proposed methodology is very effective to detect the onset of crack initiation in a non-invasive and safe way.
“…Investigations demonstrated the increase of microhardness in the joint area and of roughness parameters, which permitted the avoidance of damage during disassembly and the extension of the product life cycle. Top layer microcracks, which may transform themselves into fretting [7].…”
Section: Introductionmentioning
confidence: 99%
“…After simple mathematical adjustments and double logarithm, the cumulative function F(t) can be transformed into the form of the equation of the straight line (7).…”
mentioning
confidence: 99%
“…From the derived Relations ( 6) and (7), it is apparent that the value of the parameter of the form α is equal to the slope of the line K (12).…”
In this article, sample damage and wear of forced-in joints is presented, and their reliability evaluated. Compared were shafts without additional finish treatment, rolled shafts and those with a TiSiN coating. Tribological samples under investigation operated in rotational bending conditions. Recorded was the number of fatigue cycles at which damage might occur. Reliability indicators were plotted, which demonstrated that coated shafts are distinguished by the highest reliability and low damage intensity. Macroscopic observations of shaft surfaces demonstrated the traces of adhesive wear and, in the case of shafts without additional treatment and in the case of rolled shafts, fretting wear traces in the form of a ring comprising the entire shaft circumference. Microscopic observations showed numerous build-ups on the surface, microcracks, and the occurrence of wear products in the gap between the shaft and sleeve. The highest fatigue strength was demonstrated by shafts with a TiSiN coating. The shaft section change area was the place where fatigue wear occurred.
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