Abstract

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.

Highlights

  • Condition monitoring (CM), when correctly applied, offers high potential savings on the costs of equipment downtime and repair

  • Metallurgical analysis found that the cause of the fracture on the pinion gear was tooth root bending fatigue, which had the initiation at a Non-Metalic Inclusion (NMI)

  • The indicators are compared with the RSDabs of transmission error (TE) as this trend is considered to be usable for the damage detection

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Summary

Introduction

Condition monitoring (CM), when correctly applied, offers high potential savings on the costs of equipment downtime and repair. The cost of sensor equipment and monitoring should be considered and offset against the potential savings and, condition monitoring has conventionally been limited to high-value equipment. This convention is due to change as sensor networks, data transfer and processing are all decreasing in cost and improving in quality. Many high-value manufacturing industries already have the necessary equipment incorporated into their systems for control, protection and other features These systems only lack the application of CM as the key components of a CM system already exist within the assembly

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