Non-standard spur gear tooth profiles for improved epicyclic gear system performance in low speed applications

2017 ◽  
pp. 825-834
Author(s):  
E. Chiappetta ◽  
D. Morrey
Keyword(s):  
System Performance ◽  
Gear Tooth ◽  
Spur Gear ◽  
Gear System ◽  
Low Speed ◽  
Epicyclic Gear

On Dynamic Tooth Load and Stability of a Spur-Gear System Using the State-Space Approach

1985 ◽  
Vol 107 (1) ◽  
pp. 54-60 ◽  
Author(s):  
A. S. Kumar ◽  
T. S. Sankar ◽  
M. O. M. Osman
Keyword(s):  
State Space ◽  
Dynamic Load ◽  
Initial Conditions ◽  
Gear Tooth ◽  
Spur Gear ◽  
The State ◽  
Gear System ◽  
Computational Time ◽  
Steady State Condition ◽  
The Stability

In this study, a new approach using the state-space method is presented for the dynamic load analysis of spur gear systems. This approach gives the dynamic load on gear tooth in mesh as well as information on the stability of the gear system. Also a procedure is given for the selection of proper initial conditions that enable the steady-state condition to be reached faster, conditions that result in considerable savings in computational time. The variations in the dynamic load with respect to changes in contact position, operating speed, backlash, damping, and stiffness are also investigated. In addition, the stability of the gear system is studied, using the Floquet theory and the well-known stability conditions of difference systems.

Tooth Profile Modifications for Optimum Dynamic Load in Spur Gears Based on Pseudo-Interference Stiffness Estimation Method

2005 ◽  
Author(s):  
Monsak Pimsarn ◽  
Kazem Kazerounian
Keyword(s):  
Contact Stress ◽  
Gear Tooth ◽  
Estimation Method ◽  
Spur Gear ◽  
Rigid Body Dynamics ◽  
Gear System ◽  
Hertzian Contact ◽  
Bending Fatigue ◽  
Gear Mesh ◽  
Hertzian Contact Stress

A systematic methodology combining optimization, three dimensional analytical rigid body dynamics and a novel method, namely, Pseudo-Interference Stiffness Estimation method (PISE) [1]- [2], is proposed to dramatically reduce gear design time and improve the spur gear system dynamic performance. The main aim of this methodology is to search for the pro les of tooth crowning and shaving that eventually lead to the optimum dynamic tooth load in the gear mesh. An example of the detailed design study is numerically investigated. The results show that the dynamic tooth load can be reduced to up to 50 percent of its original value. However, this reduction is only valid at the operating ranges of the design load and design speed. It is also found that the effect of pro le modi cation on the dynamic response of the gear system was mostly observed to be a reduction in the peak dynamic tooth load at the resonance speed. Later, the investigation of gear tooth durability was conducted to validate an improvement of gear life. The rating factors given in AGMA publication, Hertzian contact stress, bending fatigue stress, ash temperature and PV index are employed in gear durability determination. The results show that, with the reduction of 50 percent in dynamic tooth load, the reductions in PV index, bending fatigue, Hertzian contact stress, and ash temperature can be achieved up to 64, 58, 28 and 39 percent, respectively.

scholarly journals Fault Feature Analysis of Gear Tooth Spalling Based on Dynamic Simulation and Experiments

Materials ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6053
Author(s):  
Zhiguo Wan ◽  
Jie Zheng ◽  
Jie Li ◽  
Zhenfeng Man
Keyword(s):  
Dynamic Model ◽  
Dynamic Simulation ◽  
Gear Tooth ◽  
Resonance Region ◽  
Spur Gear ◽  
Gear System ◽  
Parameter Method ◽  
Coupling Vibration ◽  
Shock Response ◽  
Potential Energy Method

Gear dynamics analysis based on time-varying meshing stiffness (TMS) is an important means to understand the gear fault mechanism. Based on Jones bearing theory, a bearing statics model was established and introduced into a gear system. The lateral–torsion coupling vibration model of the gear shaft was built by using a Timoshenko beam element. The lumped parameter method was used to build the dynamic model of a gear pair. The dynamic model of a spur gear system was formed by integrating the component model mentioned above. The influence of rectangular and elliptical spalling on TMS was analyzed by the potential energy method (PEM). The fault feature of tooth spalling was studied by dynamic simulation and verified by experiments. It is found that the gear system will produce a periodic shock response owing to the periodic change of the number of meshing gear teeth. Due to the contact loss and the decrease of TMS, a stronger shock response will be generated when the spalling area is engaged. In the spectrum, some sidebands will appear in the resonance region. The results can provide a theoretical guide for the health monitoring and diagnosis of gear systems.

scholarly journals Generation Mechanism and Evolution of Five-state Meshing Behavior of a Spur Gear System Considering Gear-tooth Time-varying Contact Characteristics

2021 ◽  
Author(s):  
Shi Jian-Fei ◽  
Xiang-feng Gou ◽  
Ling-yun Zhu
Keyword(s):  
Chaotic Behavior ◽  
Gear Tooth ◽  
Time History ◽  
Spur Gear ◽  
Gear System ◽  
Generation Mechanism ◽  
Load Factor ◽  
Back Side ◽  
Time Varying ◽  
Dynamic Meshing

Abstract Teeth disengaging or back-side teeth meshing induced by backlash reduces the transmission quality and dynamic performance of gear systems, and accurate interpretation of multi-state meshing behavior can provide guidance for structural optimization and performance evaluation. Therefore, the multi-state meshing behavior of the gear system is elaborated. A new nonlinear dynamic model of a spur gear system with five-state meshing behavior is proposed based on time-varying backlash and contact ratio. The time-varying meshing stiffness and time-varying backlash considering the elastic contact of gear teeth, gear temperature rise and lubrication are included in the model. The five-state meshing behavior is clearly characterized by constructing five Poincaré maps, and its generation mechanism is studied using dynamic meshing force time history, teeth relative displacement time history and phase portrait. The bifurcation and evolution of five-state meshing behavior are analyzed under the effects of load factor, meshing frequency and error coefficient. The results show that the mutation in the direction of dynamic meshing force leads to teeth disengaging and back-side single or double teeth contact, forming multi-state meshing behavior. Bifurcation caused by parameter changes greatly affects the evolution of five-state meshing behavior, particularly grazing bifurcation can decrease the number of teeth disengagement. Chaotic behavior or trajectory expansion inspires multi-state meshing vibration of the system. Previous gear system models could not reveal these phenomena due to ignoring the multi-state meshing behavior.

Modeling of surface roughness in a novel magnetorheological gear profile finishing process

2020 ◽  
pp. 095440622097826
Author(s):  
Ravi Datt Yadav ◽  
Anant Kumar Singh ◽  
Kunal Arora
Keyword(s):  
Surface Roughness ◽  
Gear Tooth ◽  
Surface Characteristics ◽  
Spur Gear ◽  
Tooth Profile ◽  
Tooth Surface ◽  
Magnetic Flux Density ◽  
Element Analysis ◽  
Finishing Process ◽  
Gear Profile

Fine finishing of spur gears reduces the vibrations and noise and upsurges the service life of two mating gears. A new magnetorheological gear profile finishing (MRGPF) process is utilized for the fine finishing of spur gear teeth profile surfaces. In the present study, the development of a theoretical mathematical model for the prediction of change in surface roughness during the MRGPF process is done. The present MRGPF is a controllable process with the magnitude of the magnetic field, therefore, the effect of magnetic flux density (MFD) on the gear tooth profile has been analyzed using an analytical approach. Theoretically calculated MFD is validated experimentally and with the finite element analysis. To understand the finishing process mechanism, the different forces acting on the gear surface has been investigated. For the validation of the present roughness model, three sets of finishing cycle experimentations have been performed on the spur gear profile by the MRGPF process. The surface roughness of the spur gear tooth surface after experimentation was measured using Mitutoyo SJ-400 surftest and is equated with the values of theoretically calculated surface roughness. The results show the close agreement which ranges from −7.69% to 2.85% for the same number of finishing cycles. To study the surface characteristics of the finished spur gear tooth profile surface, scanning electron microscopy is used. The present developed theoretical model for surface roughness during the MRGPF process predicts the finishing performance with cycle time, improvement in the surface quality, and functional application of the gears.

The Feature Extraction Method of Gear Magnetic Memory Signal

2013 ◽  
Vol 819 ◽  
pp. 206-211
Author(s):  
Yong Gang Xu ◽  
Zhi Cong Xie ◽  
Lin Li Cui ◽  
Jing Wang
Keyword(s):  
Gear Tooth ◽  
Low Frequency ◽  
Magnetic Memory ◽  
Magnetic Signal ◽  
Heavy Load ◽  
Low Speed ◽  
Feature Extraction Method ◽  
Test Technology ◽  
Time Scale Decomposition ◽  
Memory Signals

Magnetic memory test technology is a new nondestructive testing technique, which is able to detect of the stress concentration area and potential fault of low speed and heavy load gear. Because the magnetic memory signals are easy to be disturbed by various sources of noises, a new method based on the intrinsic time-scale decomposition (ITD) is proposed to achieve the extraction of magnetic memory signal. Firstly, the magnetic memory signals are decomposed into several proper rotation components (PRC) and a trend component by ITD. Then reconstruct the first four order PRCs to eliminate the low frequency cyclic composition of magnetic memory signal and magnetic noise. Finally, the magnetic signal strengths of each gear tooth root are extracted using cycle average and local statistic method. The results of Experiments show that the method is suitable to pick up effective ingredients of signal to extract signal feature and has important application value in potential fault diagnosis of low speed and heavy load gearbox.

Surface fitting of an involute spur gear tooth flank roughness measurement to its nominal shape

Measurement ◽  
2016 ◽  
Vol 91 ◽  
pp. 479-487 ◽  
Author(s):  
José A. Brandão ◽  
Jorge H.O. Seabra ◽  
Manuel J.D. Castro
Keyword(s):  
Gear Tooth ◽  
Spur Gear ◽  
Surface Fitting ◽  
Roughness Measurement ◽  
Tooth Flank

scholarly journals An implicit algorithm for the dynamic study of nonlinear vibration of spur gear system with backlash

2018 ◽  
Vol 19 (3) ◽  
pp. 310 ◽  
Author(s):  
Youssef Hilali ◽  
Bouazza Braikat ◽  
Hassane Lahmam ◽  
Noureddine Damil
Keyword(s):  
Continuation Method ◽  
Time Discretization ◽  
Contact Problems ◽  
Spur Gear ◽  
Gear System ◽  
Two Stage ◽  
Math Model ◽  
Newmark Scheme ◽  
Regularization Techniques ◽  
Taylor Series Expansions

In this work, we propose some regularization techniques to adapt the implicit high order algorithm based on the coupling of the asymptotic numerical methods (ANM) (Cochelin et al., Méthode Asymptotique Numérique, Hermès-Lavoisier, Paris, 2007; Mottaqui et al., Comput. Methods Appl. Mech. Eng. 199 (2010) 1701–1709; Mottaqui et al., Math. Model. Nat. Phenom. 5 (2010) 16–22) and the implicit Newmark scheme for solving the non-linear problem of dynamic model of a two-stage spur gear system with backlash. The regularization technique is used to overcome the numerical difficulties of singularities existing in the considered problem as in the contact problems (Abichou et al., Comput. Methods Appl. Mech. Eng. 191 (2002) 5795–5810; Aggoune et al., J. Comput. Appl. Math. 168 (2004) 1–9). This algorithm combines a time discretization technique, a homotopy method, Taylor series expansions technique and a continuation method. The performance and effectiveness of this algorithm will be illustrated on two examples of one-stage and two-stage gears with spur teeth. The obtained results are compared with those obtained by the Newton–Raphson method coupled with the implicit Newmark scheme.

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