Design and Analysis for Hypoid Gears with Ease-Off Flank Modification

An approach of ease-off flank modification for hypoid gears was proposed to improve the meshing performance of automobile drive axle. Firstly, a conjugate pinion matching with gear globally was developed based on gear meshing theory. Secondly, a modified pinion was represented by a sum of two vector functions determining the conjugate pinion and the normal ease-off deviations expressed by both predesigned transmission error function and tooth profile modification curves to change the initial contact clearance of the tooth. Thirdly, the best ease-off deviations were determined by optimizing the minimum amplitude of loaded transmission error (ALTE) based on tooth contact analysis (TCA) and loaded tooth contact analysis (LTCA). Finally, the results show that effective contact ratios (εe) are established by clearances both teeth space and of contact elliptical, and greatly affect ALTE. The εe is a variable value with increasing loads for the tooth with modification. ALTE decreases with increasing εe. After εe reaches the maximum, ALTE increases with increasing loads. The mismatch of the best ease-off tooth is minimal, which contributes to effective reduction in ALTE, thus significantly improving drive performance.

Evaluation of a Novel Condition Indicator with Comparative Application to Hypoid Gear Failures

This paper presents a condition monitoring methodology that uses a novel condition indicator (CI) algorithm, allowing for a confident assessment of system health and an advanced warning of failures. The CI is evaluated in the application of a specialized gear rig utilized for the high-cycle fatigue testing of hypoid gears. The CI is shown in this case study to ensure higher confidence in the prediction of failures than other algorithms, with variations in the results. In the comparison, consideration is given to the signal-to-noise ratio, the ability to differentiate between damages and/or damaged components and the sensitivity of the CI to the failure.

Data-driven process control for manufacturing spiral bevel and hypoid gears by using design for six sigma (DFSS) considering numerical loaded tooth contact analysis (NLTCA)

Data-driven process control considering both geometric and loaded contact performance evaluations has been an increasingly important stage in field of spiral bevel and hypoid gears. A new data-driven manufacturing process control strategy is proposed for a high performance spiral bevel and hypoid gears. Here, to distinguish with the conventional simulated loaded tooth contact analysis (SLTCA) using economical finite element software package, the numerical loaded tooth contact analysis (NLTCA) is of more flexibility and practicality. In light of the advantages of the improved design for six sigma (DFSS), it is integrated with NLTCA for establishing a novel data-driven process control of gear manufacturing. Firstly, in improved DFSS framework, quality function deployment (QFD) is used to determine four sub-objective high-performance evaluation items. Then, their data-driven relationships between machine settings are respectively determined by using NLTCA. In particular, the manufacturing process control is further converted into multi-objective optimization (MOO) modification of the hypoid generator settings. Finally, an interactive preference point approach is applied for data-driven control of its iterative step and it can obtain a robust solution from Pareto optimal front. A case study is provided to verify the proposed methodology.