A new approach to predicting bearings failure

Stock image: 123rf.com |- electric power plant

Detecting mechanical faults in bearings and machinery has long been recognised as being important for preventing catastrophic failure and effective maintenance planning.

The human senses of sound and touch were the first mechanisms used to detect machinery problems. Electronic sensors have since offered the ability to feel and listen to machinery with more precision, at more locations and over more time than was ever before possible. Interpretation of the electronic signals delivered by these sensors has provided the maintenance engineer with the diagnostic information necessary to pinpoint bearing faults, thus enabling a more efficient and predictable maintenance effort.

However, skilled and trained personnel have been required to effectively interpret this diagnostic information. As electronic sensors have become more sophisticated, so too have the diagnostic techniques, leading to the ability of earlier detection of failures with less required skill.

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