BS-ISO helical gear fatigue life estimation and wear quantitative features analysis

Original article can be found at: http://www3.interscience.wiley.com/ Copyright Blackwell Publishing. DOI: 10.1111/j.1475-1305.2008.00457.xLack of representative theoretical models for gear wear causes difficulties in their useful lifetime prediction. Critical operating parameters, such as loading and lubrication, affect the wear process in a very complex manner and lead the theoretical modelling to an imperfect zone of assumptions. Complexities in gear wear mathematical modelling allow the researchers to use approximations for useful lifetime calculations. On the basis of modelling approximations and assumptions, organizations, such as American Gear Manufacturers' Association (AGMA) and British Standards (BS), provide gear useful lifetime formulations. In these formulations, the useful lifetime values are estimated by means of experimentation that is controlled with known gear operating conditions and physical dimensions. However, for useful lifetime estimation and validation, these standards have not considered any experimental approach that represents the actual gear wear. In this paper, an effort is made to validate the competency of standard's gear useful lifetime formulation. For this purpose, an approach that is able to provide an idea about actual gear wear is used. During the effort, BS-ISO 6336-2 standard formulation is used for helical gear useful lifetime estimation under linear pitting fatigue conditions. The used formulation is validated by using wear quantitative feature analysis that is able to provide actual gear wear quantitative trends. The obtained wear quantitative trends fairly validate the lifetime estimation of BS-ISO 6336-2 standard.Peer reviewe

Gear wear process monitoring using acoustic signals

Airborne acoustic signals contain valuable information from machines and can be detected remotely for condition monitoring. However, the signal is often seriously contaminated by various noises from the environment as well as nearby machines. This paper presents an acoustic based method of monitoring a two stage helical gearbox, a common power transmission system used in various industries. A single microphone is employed to measure the acoustics of the gearbox under-going a run-to-failure test. To suppress the background noise and interferences from nearby ma-chines a modulation signal bispectrum (MSB) analysis is applied to the signal. It is shown that the analysis allows the meshing frequency components and the associated shaft modulating components to be captured more accurately to set up a clear monitoring trend to indicate the tooth wear of the gears under test. The results demonstrate that acoustic signals in conjunction with efficient signal processing methods provide an effective monitoring of the gear transmission process

Transmission characteristics of planetary gear wear in multistage gear transmission system

Gear tooth surface wear is a common failure mode. It takes a long time and can cause other major faults. The wear fault signal is weak and hard to identify. This paper reveals the transmission characteristics of the planetary gear wear and the relationship between multistage gear meshing through the transmission characteristic analysis. Taking the multistage gear transmission system fault simulation test rig as the research object, a three-dimensional solid rigid-flexible coupling model of the system was established. The contact force signals from each pair of gears in the state of planetary gear wear were obtained by dynamic simulation. The test signals of the fixed-axis gearbox and planetary gearbox were obtained under normal and planetary gear wear states. Comparing the transmission characteristics of the system under normal and planetary gear wear states, the vibration mechanism of the wear fault and the correlative characteristic between gearboxes were revealed

Gear wear process monitoring using a sideband estimator based on modulation signal bispectrum

As one of the most common gear failure modes, tooth wear can produce nonlinear modulation sidebands in the vibration frequency spectrum. However, limited research has been reported in monitoring the gear wear based on vibration due to the lack of tools which can effectively extract the small sidebands. In order to accurately monitor gear wear progression in a timely fashion, this paper presents a gear wear condition monitoring approach based on vibration signal analysis using the modulation signal bispectrum-based sideband estimator (MSB-SE) method. The vibration signals are collected using a run-to-failure test of gearbox under an accelerated test process. MSB analysis was performed on the vibration signals to extract the sideband information. Using a combination of the peak value of MSB-SE and the coherence of MSB-SE, the overall information of gear transmission system can be obtained. Based on the amplitude of MSB-SE peaks, a dimensionless indicator is proposed to assess the effects of gear tooth wear. The results demonstrated that the proposed indicator can be used to accurately and reliably monitor gear tooth wear and evaluate the wear severity

Continued Evaluation of Gear Condition Indicator Performance on Rotorcraft Fleet

This paper details analyses of condition indicator performance for the helicopter nose gearbox within the U.S. Army's Condition-Based Maintenance Program. Ten nose gearbox data sets underwent two specific analyses. A mean condition indicator level analysis was performed where condition indicator performance was based on a 'batting average' measured before and after part replacement. Two specific condition indicators, Diagnostic Algorithm 1 and Sideband Index, were found to perform well for the data sets studied. A condition indicator versus gear wear analysis was also performed, where gear wear photographs and descriptions from Army tear-down analyses were categorized based on ANSI/AGMA 1010-E95 standards. Seven nose gearbox data sets were analyzed and correlated with condition indicators Diagnostic Algorithm 1 and Sideband Index. Both were found to be most responsive to gear wear cases of micropitting and spalling. Input pinion nose gear box condition indicators were found to be more responsive to part replacement during overhaul than their corresponding output gear nose gear box condition indicators

Helical gear wear monitoring: Modelling and experimental validation

Gear tooth surface wear is a common failure mode. It occurs over relatively long periods of service nonetheless, it degrades operating efficiency and leads to other major failures such as excessive tooth removal and catastrophic breakage. To develop accurate wear detection and diagnosis approaches at the early phase of the wear, this paper examines the gear dynamic responses from both experimental and numerical studies with increasing extents of wear on tooth contact surfaces. An experimental test facility comprising of a back-to-back two-stage helical gearbox arrangement was used in a run-to-failure test, in which variable sinusoidal and step increment loads along with variable speeds were applied and gear wear was allowed to progress naturally. A comprehensive dynamic model was also developed to study the influence of surface wear on gear dynamic response, with the inclusion of time-varying stiffness and tooth friction based on elasto-hydrodynamic lubrication (EHL) principles. The model consists of an 18 degree of freedom (DOF) vibration system, which includes the effects of the supporting bearings, driving motor and loading system. It also couples the transverse and torsional motions resulting from time-varying friction forces, time varying mesh stiffness and the excitation of different wear severities. Vibration signatures due to tooth wear severity and frictional excitations were acquired for the parameter determination and the validation of the model with the experimental results. The experimental test and numerical model results show clearly correlated behaviour, over different gear sizes and geometries. The spectral peaks at the meshing frequency components along with their sidebands were used to examine the response patterns due to wear. The paper concludes that the mesh vibration amplitudes of the second and third harmonics as well as the sideband components increase considerably with the extent of wear and hence these can be used as effective features for fault detection and diagnosis

New mode switching algorithm for the JPL 70-meter antenna servo controller

The design of control mode switching algorithms and logic for JPL's 70 m antenna servo controller are described. The old control mode switching logic was reviewed and perturbation problems were identified. Design approaches for mode switching are presented and the final design is described. Simulations used to compare old and new mode switching algorithms and logic show that the new mode switching techniques will significantly reduce perturbation problems

Gear wear-monitoring using acoustic emission

Acoustic emission (AE) signals have shown strong potential for gear wear monitoring, because of their capability of capturing high-frequency characteristics of tribological contacts. Gear AE signals are characterised by: i) short-time features coming from the complex surface micro-structure (asperities) and ii) slower cyclic features introduced by the gear kinematics. The combination of both properties has not been exploited yet, thus leaving a significant margin for the development of AE-based gear monitoring. This thesis hence aims at developing novel AE-based gear wear monitoring tools through the investigation of the statistical properties of gear AE as well as the physical relationships between signals and gear surface conditions. This research is organised in three steps to deliver the following objectives. Step 1 is to establish the relationship between AE signals and cyclic gear kinematics, modelled using AE cyclostationarity. Differently from the next steps, this approach purposely avoids an onerous physical model, and instead uses non-Gaussian statistics to represent the micro-structure effects on AE. Results show that the newly-developed cyclic AE features are highly correlated with wear severity. The physical modelling is tackled in step 2, which investigates the link between AE and micro-scale surface conditions, independently on gear kinematics. Two available physical models for dry contact are extended to lubricated sliding, and then tested on tribometer discs with different surface finishing. The pin-on-disc configuration avoids the complex gear kinematics, facilitating the direct study of surface effects under stable speed and load. The new physical model was able to reliably estimate roughness in a series of tests with different operating conditions. In the final step, the gear-kinematic effects modelled in step 1 are superimposed to the physical relationship between surface and signals observed in step 2 for a further investigation on the relationship between AE and gear wear. A set of experiments on degrading gears has proven that the proposed techniques are able to track gear wear along tooth profiles as it evolves in time. Furthermore, this study contributed to the understanding of the impact of surface characteristics on specific AE features, opening new avenues for further developments of AE-based gear wear monitoring