Gear tooth breakage due to bending fatigue is one of the most dangerous failure modes of gears. Therefore, the precise definition of tooth bending strength is of utmost importance in gear design. Single tooth bending fatigue (STBF) tests are usually used to study this failure mode since they allow to test gears, realized and finished with the actual industrial processes. Nevertheless, STBF tests do not reproduce exactly the loading conditions of meshing gears. The load is applied in a predetermined position, while in meshing gears, it moves along the active flank; all the teeth can be tested and have the same importance, while the actual strength of a meshing gear, practically, is strongly influenced by the strength of the weakest tooth of the gear. These differences have to be (and obviously are) taken into account when using the results of STBF tests to design gear sets. The aim of this article is to investigate in detail the first aspect, i.e. the role of the differences between two tooth root stress histories. In particular, this article presents a methodology based on high-cycle multi-axial fatigue criteria to translate STBF test data to the real working condition; residual stresses are also taken into account.

Mechanical components, such as gears, are usually subjected to variable loads that induce multiaxial non-proportional stress states, which in turn can lead to failure due to fatigue. However, the material properties are usually available in the forms of bending or shear fatigue limits. Multiaxial fatigue criteria can be used to bridge the gap between the available data and the actual loading conditions. However, different criteria could lead to different results. The main goal of this paper is to evaluate the accuracy of different criteria applied to real mechanical components. With respect to this, five different criteria based on the critical plane concept (i.e., Findley, Matake, McDiarmid, Papadopoulos, and Susmel) have been investigated. These criteria were selected because they not only assess the level of damage, but also predict the direction of crack propagation just after nucleation. Therefore, measurements (crack position and direction) on different fractured gear samples tested via Single Tooth Bending Fatigue (STBF) tests on two gear geometries were used as reference. The STBF configuration was numerically simulated via Finite Elements (FE) analyses. The results of FE were elaborated based on the above-mentioned criteria. The numerical results were compared with the experimental ones. The result of the comparison showed that all the fatigue criteria agree in identifying the most critical point. The Findley and Papadopulus criteria proved to be the most accurate in estimating the level of damage. The Susmel criterion turns out to be the most conservative one. With respect to the identification of the direction of early propagation of the crack, the Findley criterion revealed the most appropriate.

The introduction of Additive Manufacturing (AM) is changing the way in which components and machines can be designed and manufactured. Within this context, designers are taking advantage of the possibilities of producing parts via the addition of material, defining strategies, and exploring alternative design or optimization solutions (i.e., nonviable using subtractive technologies) of critical parts (e.g., gears and shafts). However, a safe and effective design requires specific resistance data that, due to the intrinsic modernity of additive technologies, are not always present in the literature. This paper presents the results of an experimental campaign performed on gear-samples made by 17-4 PH and produced via Laser Powder Bed Fusion (PBF-LB/M). The tests were executed using the Single Tooth Bending Fatigue (STBF) approach on a mechanical pulsator. The fatigue limit was determined using two different statistical approaches according to Dixon and Little. The obtained data were compared to those reported in the ISO standard for steels of similar performance. Additional analyses, i.e., Scanning Electron Microscopy SEM, were carried out to provide a further insight of the behavior 17-4PH AM material and in order to investigate the presence of possible defects in the tested gears, responsible for the final failure.

Classical machine elements have been around for centuries, even millennia. However, the current advancement in Structural Health Monitoring (SHM), together with Condition Monitoring (CM), requires that machine elements should be upgraded from a not-simple object to an intelligent object, able to provide information about its working conditions to its surroundings, especially its health. However, the integration of electronics in a mechanical component may lead to a reduction in its load capacity since the component may need to be modified in order to accommodate them. This paper describes a case study, where, differently from other cases present in the literature, sensor integration has been developed under the gear teeth of an actual case-hardened helical gear pair to be used within an actual gearbox. This article has two different purposes. On the one hand, it aims to investigate the effect that component-level SHM/CM has on the gear load carrying capacity. On the other hand, it also aims to be of inspiration to the reader who wants to undertake the challenges of designing a sensor-integrated gear.

Due to their cost-effectiveness, pulsator tests are widely adopted as a testing methodology for the investigation of the effects of material and heat and surface treatment on the gear strength with respect to tooth root fatigue fracture. However, since no meshing contact is present in pulsator tests, there are differences between the test case and the real-world application scenario where gears are rotating under load. Those differences are related to both statistical and fatigue phenomena. Over the years, several methodologies have been developed in order to handle this problem. This article summarizes them and proposes a first comparison. However, no complete comparison between the different estimation methodologies has been conducted so far. This article aims to partially cover this gap, first by presenting and comparing the methodologies proposed in the literature and then via a deeper comparison between two different elaboration methodologies. Those two methodologies, which have been developed by examined to the same test rig configuration, are also discussed in detail. The comparison is performed based on an actual database composed of 1643 data points from case-hardened gears, divided into 76 experimental campaigns. Good agreement between the estimated gear strengths was found. The database is also adopted in order to make further considerations about one methodology, providing additional validation and defining the specimen numerosity required.