diagnostician and practitioner, working at the Ecol Oil Analysis Laboratory, responsible for the interpretation of test results and customer support in the area of lubricant analysis.
In previous article we have presented an introduction to statistical analysis of results from oil tests and information, which are provided by regular lubricant analysis. In today’s publication we will try to find the answer to recently asked question:
How to determine an optimal alarm values, useful for wind farm operators?
For this purpose we will use a graph showed in previous paper.
In the first step, it is necessary to determine the mean and standard deviation (sigma – σ) for a given population of results. It is also worth rejecting extremely high results at the beginning, if any, because they significantly affect the standard deviation and can falsify the finally determined ranges. When selecting the results for analysis, the graph is very helpful, where you can see the abnormal results at first glance. Using these two statistical values, we are able to determine approximate alarm limits for wear parameters. The diagram of normal distribution, already known to you, is presented below, but with additionally marked alarm ranges. The process of their evaluation is explained later in this article.
Rys. 1. Standard distribution of iron content in analyzed sample population.
As can be seen from the chart, most of the results (approx. 90%) are in the range of 0 ÷ 40 ppm. Therefore, we conclude that the iron content within the given limits, can be considered normal and not indicating any disturbing wear processes in the gearbox. On the other hand, after calculating the mean and standard deviation, we can estimate the relevant limits for the iron content in the considered gearboxes. In our laboratory, we have established a three-level grading scale for use: NORMAL, CAUTION and ACTION. The obtained results are presented in the table below:
According to ASTM D7720 standard, “the green” range should be between 0 and the mean value plus two standard deviations (+ 2σ). A slight exceeding of the permissible limits may indicate, for example, the necessity to checking the correctness operation of the gear, checking other parameters (temperature, vibrations, noise) and send a control sample for analysis. On the other hand, extreme exceeding the limit values most often leads to specific service actions – oil change and gear inspection in order to detect potential wear.
In this case, the statistic analyze stand by our side. Having a sufficiently large population of results (the more numerous – the more precise ranges will be) we have the opportunity to obtain valuable data. However, we should keep in mind that these are indicative values and cannot always be taken as certainty – besides established alarm limits, the trend changes in the parameter over time is also very important during the assessment. We will focus on analyze of trend changes, supplemented by statistical analysis in the next publication. Only by assessing the dynamics of changes in parameters during operation and relating it to the adopted limits, we have a clear diagnostic view on the operating machines.
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