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Developing Nuclear Maintenance Decisions through Systematic Use of Machine Vibration Data, PDM Technologies


by George D’Entremont

Abstract


This paper gives an example of a systematic process used by a vibration analyst to develop maintenance decisions from information available in a facilities vibration data base. The specific process described is in use at a nuclear facility, but is applicable to any facility with an established predictive maintenance program using vibration analysis, but may also be applied to established oil analysis or other PdM technologies. The systematic process is not intended to replace the analysts’ knowledge or experience but to provide a process that will improve the analysts’ ability to determine where their efforts should be concentrated and developing consistent and reliable maintenance decision recommendations from that information. This paper would be especially applicable to personnel involved with development of a program (beginner) to intermediate level programs that are evaluating how to improve their present processes. The paper provides examples of a Vibration Threshold Table, a Vibration Review Datasheet, and a Machine Fault Matrix. This is a very practical paper to assist Analysts and Engineers in evaluating possible improvements for their PdM programs.

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“Purpose and Scope:

This paper suggests systematic steps by which machine casing vibration data may be used to create maintenance decisions at a nuclear electric generating station. The paper is, in part, a response to topics discussed during meetings conducted in Japan by the Electric Power Research Institute (EPRI) with their Japanese members in May 2010. These discussions related to the use of systematic review and evaluation techniques that promote the most accurate maintenance decisions.

Once elements of Reliability-Centered Maintenance have been implemented at a nuclear station, many condition-directed maintenance tasks will be triggered by the results of machine vibration analysis. It becomes important, then, to understand the actions that should be taken by the vibration analyst in response to observed vibration data. Although a trained analyst may likely identify indications of early stage machine degradation through vibration data, his ability to confirm and communicate his observations in a manner that protects critical station functions warrants further attention. A vibration analyst, confronted with a large and expanding vibration database, may be overcome with questions of where he should concentrate his attention and what actions he should take to insure important data is not ignored. This paper presents a distilling technique, which reduces information from an existing vibration database in a manner that yields necessary maintenance decisions. It is not the intent to present this as an EPRI-recommended approach. It is, instead, offered as an example of one such approach taken at a US nuclear station.

The technique begins with the creation of action thresholds for vibration. These thresholds, once exceeded, prompt the analyst to take the following steps:

Step 1

Confirm the vibration condition

Step 2

Review vibration and other data

Step 3

Evaluate the vibration condition against likely causes

Step 4

Report evaluation results to the station organization

Step 5

Inspect forensic results

"Discussion:

In adopting principles of Reliability-Centered Maintenance, it is important for the vibration analyst to remain mindful that his inspections serve to protect critical system functions that may no longer be protected by time-directed maintenance. His activities are not mere enhancements to scheduled maintenance. Recommendations resulting from his inspections may now be the single barrier against critical equipment failure.

Effective vibration analysis owes much to the ability of the individual analyst. This is an inescapable characteristic of the discipline. As a result, vibration evaluation may appear subjective… relying heavily on the intuition or whim of the individual analyst, and without scientific-like substance.”

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