This paper, by the experimental investigation, deals with the effect of different surface topographies on noise generation in gears. Results from the noise assessment of one gear before and after honing are discussed. The honing operation was applied to the gear after the grinding. The gear was tested in an actual gearbox, operated in a test rig. Running conditions were systematically changed during the test; however, the same conditions were utilized for the gear before and after honing. The aim of the study was to identify the mechanism of the expected noise reduction, with surfaces being evaluated in 3D. The following results have been obtained: The total energy in the noise decreases significantly. The magnitude of the tooth-mesh frequency dose not change, but the level of its higher harmonics decreases significantly. These reductions are especially significant, when running at higher rotational speeds or when the applied torque is increased.

This paper describes a dynamic model for gear transmissions acting around a static working point, and taking into account the complete mechanical components. Gearbox casing behavior is introduced by using substructure analysis, and a tangent stiffness matrix is defined for each roller body bearing element. This model is used to compare the pullup and pulldown dynamic behavior of a five speed medium size automobile gearbox where the gear meshing phenomena are assumed to be identical. The eigenmodes of the pullup and pulldown models are compared and frequency responses to meshing excitation are studied. Substantial differences between pullup and pulldown behavior are observed and associated with to the orientation of static load.

This paper describes the application of neural networks to gearbox fault diagnosis. In order to increase learning speed of BP network, a modified learning algorithm was presented. Considering of the difficulty of choosing neural networks’ architecture, genetic algorithm was employed. The discussion of the effect of hidden layer nodes shows that with the increase of the number of nodes, the learning speed increase also yet result in poor generalization ability. The test of fault tolerance ability tells that neural networks have ‘bench type’ tolerance ability. This ensures that when signals were contaminated by noise or feature extraction methods were not effective, the result can still be acceptable. To test the performance of the application of neural networks on gearbox fault diagnosis, experiments of single fault and multi-faults were both implemented and diagnosed by neural networks. The results were satisfied.

Gears, bearings, springs, fasteners etc. are some typical machine elements used to build machines and mechanical systems. These elements are used for performing one or more of functions such as, to transmit motion, to support moving members, to store energy, to join two components etc. The continuous miniaturization and the need for mechanical systems having sizes of a few nanometers have led to new but challenging issues in design and manufacturing of these machine elements. Carbon nanotubes have a potential to be used as machine elements in multiple roles for building mechanical systems at a nano level. This paper explores the use of single-walled and multi-walled carbon nanotubes in building a nano-mechanical system such as gearbox . The paper presents a conceptual design of a gearbox completely made of carbon nano tubes and discusses its feasibility and realizability. The paper also discusses future directions of research in building nanomachines and nano-mechanical systems using carbon nanotube based machine elements.

In this paper a step-by-step procedure for carrying out synthesis of geometric tolerances of a planetary gearbox using a deviation-based tolerance synthesis (TS) scheme has been presented. The TS scheme uses an optimization for minimizing total cost of manufacturing, subject to constraints for assemblability of parts and constraints for functional requirements. The TS work is carried out in several stages. First the gearbox with its nominal dimensions is converted into a model that could serve as input to the synthesis module. Cost functions and constraints equations are then generated using deviation parameters of features. The optimization is carried out using these equations in standard non-linear minimization tools (Matlab) and the optimal deviation parameters are subsequently mapped into suitable tolerance specifications or tolerance zones as per ANSI Y14.5 tolerancing standards.

The Internet and World Wide Web (WWW) are now evolving as an important communication technology and a major information resource provider for industry. This paper discusses the development and implementation of a knowledge-based gear design and manufacturing system over the Internet to create new integrated design and manufacturing environments. By providing access to an interactive web-based support system, any designer with a WWW browser becomes a potential user of this on-line design system. Once connected, the designer follows the system instructions and submits the necessary input data on the appropriate web pages. The server receives a request from a client and invokes a CGI (Common Gateway Interface) program that processes the information provided through the user Interface. The CGI parses the data and has the ability to remotely run the knowledge-based gear design system that integrates knowledge about all aspects of gear design and manufacturing and provides powerful reasoning and decision-making capabilities for reducing the time between gear tooth creation, detailed design and manufacturing process specification via the Internet. When the execution is completed, full specifications definition, geometry, kinematic-loads and stresses are determined through Finite Element Analysis (FEA) within ANSYS, VRML models of the gear pair and gearbox assembly including gears, shafts, bearings and housing are exported according to the designer requests and sent back to designer on the web browser. To accomplish this, a combination of HTML, JavaScript, VRML, CGI Script and C++ is used. Finally, an example on spur gear design utilizing a parallel gearbox design model configuration is discussed.