Reference Information
Key information from reference documents and guides (e.g.) or succinct descriptions of concepts (e.g. what is risk and how do I visualize it)
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Research & Technical Content
Key takeaways, results from ongoing research tasks, and how they are applied.
1 - Research Result Summaries
Latest results from ongoing tasks
A Study of Silicone Rubber Coated Glass Insulators: Comparing the Performance of Fully Coated and Bottom Coated Insulators
EPRI performed salt fog testing on glass insulator that were fully coated with silicone rubber and bottom coated only to learn how they performed. This knowledge can help utilities be better informed about the options being presented to them.
Lessons Learned from Porcelain Insulator Failures
EPRI performs failure assessment of insulators regularly. This report describes the trends identified from tracking failures and some lessons learned from detailed studies.
A Study of How Glass Insulators Break
EPRI performs failure assessment of insulators regularly. This report describes the trends identified from tracking failures and some lessons learned from detailed studies.
2 - Reference Information
Key information from reference documents and guides (e.g.) or succinct descriptions of concepts (e.g. what is risk and how do I visualize it)
Overview and Terminology of Porcelain and Glass Insulators
A suspension insulator, which is sometimes referred to as a “disk insulator” or “bell” is defined by ANSI C29.1 as an insulator with attached metal parts having means for non-rigidly supporting electric conductors. In the IEC standards this insulator type is identified as “cap and pin insulator”, but this term in conflict with ANSI C29.1 in which “cap and pin” identifies a different kind of insulator.
Key Processes of the Contamination Flashover Process
This table shows the 8 step process leading to contamination flashover.
3 - Videos
Updates on tasks or tests
Insulator Population Assessment
Insulator populations are approaching end of design life for many utilities but pressures to maximize the life of components has them basing replacement on condition rather than time. This video describes one of the test ares in EPRI’s lab for assessing insulator conditions and collecting the mush needed information for utilities to make condition based decisions.
3.1 - Insulator Population Assessment
Insulator populations are approaching end of design life for many utilities but pressures to maximize the life of components has them basing replacement on condition rather than time. This video describes one of the test ares in EPRI’s lab for assessing insulator conditions and collecting the mush needed information for utilities to make condition based decisions.
4 - Calculators
Software applications to support quick calculations
Mechanical Failing Tensile Load Assessment
To help a utility determine if a population is at risk of incurring insulator failures, a statistical approach is used.This tool lets the user explore how the test data affects the statistical population assessment of insulators.
4.1 - Mechanical Failing Tensile Load Assessment
To help a utility determine if a population is at risk of incurring insulator failures, a statistical approach is used.
This tool lets the user explore how the test data affects the statistical population assessment of insulators.
The tool presents several results calculated from the input data.
- Mean
Average test strength of the tested insulators. - Standard Deviation
Variation of the test results about the mean value. - Population Standard Deviation
Sample standard deviation multiplied by the square root of the sample size (√n). - 95% Confidence Interval
95% confidence the population mean will be within this interval. - Withstand Strength
Three population standard deviations below the mean strength or 99.985% probability. - Percent of strings to fail below line load
Percent of the normal distribution of the population that is below a specific value.
The larger the standard deviation, the wider the distributed spread of the predicted results. In practical terms, this raises the risk of failure at a specified mechanical load compared to a smaller standard deviation. The charts presented in the statistical analyses below show a cumulative distribution risk. The slope of the curve is higher for small standard deviation (i.e., most insulator test in a small range) and the slope is lower for large standard deviation (i.e., insulators can test across a large range).
For the population estimate, the mean value of the population is taken as the lower value of the 95% Confidence Interval. Therefore, two issues arise when the interval is large:
When the 95% confidence interval is large, more samples should be collected in attempt to shrink the interval.
There are three options for the source of data used in the calculation.
- “Load Sample” uses sample data from Chapter 8 of the EPRI report number 1015277. This data consists of 10 strings, each 14 disks in length.
- “Random Generation” creates randomized data centered around the user specified mean value within the user specified standard deviation. The number of strings and string length are also user specified.
- “Custom Data” lets the user input a 2-D array of information. The array must be structured as shown in the below example of 4 string 5 disks long. Two outside square brackets enclose the data. Each set of inside square brackets represents the string speratated by a comma. Within the inside square brackets are the data for each disk also seperated by a comma.
The length of each string does not have to be identical.
[[Disk 1, Disk 2, Disk 3, Disk 4, Disk 5],
[Disk 1, Disk 2, Disk 3, Disk 4, Disk 5],
[Disk 1, Disk 2, Disk 3, Disk 4, Disk 5],
[Disk 1, Disk 2, Disk 3, Disk 4, Disk 5]]
Choose the type of input you wish to use.
| Inputs for random generation: | |
|---|---|
| Number of Strings: | |
| String Length: | |
| Mean: | |
| Standard Deviation: | |