Abstract
Reliable condition indicators are necessary to perform effective diagnosis and prognosis. However, the vibration signals are often corrupted with non-Gaussian noise and rotating machines may operate under time-varying operating conditions. This impedes the application of conventional condition indicators. The synchronous average of the squared envelope is a relatively simple yet effective method to perform fault detection, fault identification and fault trending under constant and time-varying operating conditions. However, its performance is impeded by the presence of impulsive signal components attributed to impulsive noise or the presence of other damage modes in the machine. In this work, it is proposed that the synchronous median of the squared envelope should be used instead of the synchronous average of the squared envelope for gearbox fault diagnosis. It is shown on numerical and experimental datasets that the synchronous median is more robust to the presence of impulsive signal components and is therefore more reliable for estimating the condition of specific machine components.
Highlights
Condition-Based Maintenance (CBM) is needed to ensure that expensive assets such as wind turbines can perform reliably and cost-effectively
The performance of CBM depends on the ability of the fault diagnosis techniques to accurately identify the condition of the different mechanical components while the machine is operating under its normal operating conditions
Many machines found in the power generation and mining industries operate inherently under time-varying operating conditions, which impede the performance of conventional fault diagnosis techniques and reliable techniques are required to perform fault diagnosis, i.e., fault detection, fault localisation and fault trending [3,4]
Summary
Condition-Based Maintenance (CBM) is needed to ensure that expensive assets such as wind turbines can perform reliably and cost-effectively. This subtle change (i.e., using the median statistic as opposed to the mean statistic) has significant benefits when performing condition monitoring on rotating machines This is because even if the rotating machine under consideration does not operate in impulsive noise environments, non-synchronous damaged components (e.g., a damaged bearing when the pinion is interrogated) impede the performance of the SASE, but not the performance of the SMSE. This is attributed to the fact that the median is a more robust measure of the central tendency of a random variable than the mean.
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