Predictive maintenance strategies are established in the industrial context on account of their benefits in terms of costs abatement and machine failures reduction. Among the available techniques, vibration-based condition monitoring (VBCM) has notably been applied in many bearing fault detection problems. The health indicators construction is a central issue for VBCM, since these features provide the necessary information to assess the current machine condition. However, the relation between vibration data and its sources intimately related to bearing damage is not effortlessly definable from a diagnostic perspective. This study discloses a diagnostic investigation performed both on the vibration signal and on the contact pressure signal that is supposed to be one of main forcing terms in the dynamic equilibrium of the damaged bearing. Envelope analysis and spectral kurtosis (SK) are applied to extract and compare diagnostic features from both signals, referring to the Case Western Reserve University (CWRU) case-study. Namely, health indicators are constructed by means of physical considerations based on the effect of faults on the signal power contents. These indicators show to be promising not only for damage detection but, also, for damage severity assessment. Moreover, they provide an invaluable reading key of the link occurring between the contact pressure path and the vibration response.

In this paper, a review of the evolution of the study of cylindrical gear dynamics is presented. After a brief historical introduction to the field, the first attempts to describe the complex interactions in those systems are analyzed introducing the dynamic factor and the first methodologies used to compute it. Next, the sources of excitation in geared systems are analyzed in detail and the models of the various contributions are discussed. Then, the paper focuses on the use of those sources in several dynamic models which are wildly different in terms of scope, applicability, complexity and methodology employed, ranging from simple analytical models, to lumped masses models up to multibody and finite element models. Finally, an outlook to the future evolution of the field is given and conclusions are drawn.

Bearing is a crucial component of industrial equipment, since any fault occurring in this system usually affects the functionality of the whole machine. To manage this problem, some currently available technologies enable the remote prognosis and diagnosis of bearings, before that faults compromise the system function and safety, respectively. A system for the in-service monitoring of bearing, to detect any inner fault or damage of components and material, allows preventing undesired machine stops. Moreover, it even helps in performing an out-monitoring action, aimed at revealing any anomalous behaviour of the system hosting bearings, through their dynamic response. The in-monitoring can be based on the vibration signal measurement and exploited to detect the presence of defects in material. In this paper, the orthogonal empirical mode decomposition is analysed and tested to investigate how it could be effectively exploited in a lean in-service monitoring operation and remote diagnosis. The proposed approach is validated on a test rig, where an elementary power transmission line was set up. The activity highlights some main properties and practical issues of the technological implementation, as well as the precision of the Orthogonal Empirical Mode Decomposition, as a compact approach for an effective detection of bearing faults in operation.

In this paper, a three-dimensional model for the estimation of the deflections, load sharing attributes, and contact conditions will be presented for pairs of meshing teeth in a spur gear transmission. A nonlinear iterative approach based on a semi-analytical formulation for the deformation of the teeth under load will be employed to accurately determine the point of application of the load, its intensity, and the number of contacting pairs without a priori assumptions. At the end of this iterative cycle the obtained deflected shapes are then employed to compute the pressure distributions through a contact mechanics model with non-Hertzian features and a technique capable of obtaining correct results even at the free edges of the finite length contacting bodies. This approach is then applied to a test case with excellent agreement with its finite element counterpart. Finally, several results are shown to highlight the influence on the quasi-static behavior of spur gears of different kinds and amounts of flank and face-width profile modifications.

In this study the dynamic response of a spur gear pair is analyzed using a novel nonlinear approach. The actual rolling motion and engagement of the system is simulated using a set of reduced order models obtained in a pre-processing phase using the minimal amount of master degrees of freedom without loss of accuracy or generality. The flexibility of the gear bodies is included by a refined finite element model, and no geometry simplification is introduced while also retaining all nonlinearity sources. To reduce the computational cost the time-varying mesh stiffness is also pre-computed and used depending on the instantaneous loading conditions. Contact loss is also taken into account, and reconnection events are treated as vibro impacts. The results are compared against high quality and demanding experimental results with a computational cost several orders of magnitude lower than models with similar accuracy. Different loading conditions are investigated during the sweep-up and down maneuvers. Mainly, the dynamic transmission error is analyzed, showing remarkable agreement with the test campaign’s results. Different nonlinear phenomena such as hysteretic jumps and sub- and super-harmonic resonances are correctly predicted by the proposed model in terms of both frequency and amplitude. This method allows quick and accurate nonlinear analyses overcoming current limitations and is open to further complications to include other components and effects.