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Related Concept Videos

Median01:08

Median

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Besides mean, the median is a widely used measure of central tendency. Typically, median is defined as the central or middle value of a data set, measured by arranging the data elements in an increasing or decreasing order. Since this middle value is not affected by the precise numerical values of the outliers or fluctuations, it is insensitive to them. Hence, in cases where a data set may have outliers or the extreme values are not known, the median is a better measure of the central tendency...
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Sign Test for Median of Single Population01:20

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In general, the sign test serves as a nonparametric method to test hypotheses about the median of a single population when the data does not follow a known distribution. This simplicity makes it particularly useful for small sample sizes or when the assumptions of parametric tests cannot be met. The process begins with identifying a null hypothesis, typically stating that the population median equals a specific value. The alternative hypothesis could be that the median is either not equal to,...
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Passive Filters01:27

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Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
Low-Pass Filters
Low-pass filters are designed to transmit signals with frequencies lower than the cutoff frequency, ωc, and attenuate those above it. The cutoff...
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Active Filters01:25

Active Filters

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Active filters are electronic circuits that use operational amplifiers (op-amps), resistors, and capacitors to filter out unwanted frequency components from a signal. A first-order low-pass active filter is designed to pass signals with a frequency lower than a certain cutoff frequency and attenuate frequencies higher than that cutoff frequency. The transfer function for a first-order low-pass active filter is:
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Wilcoxon Signed-Ranks Test for Median of Single Population01:14

Wilcoxon Signed-Ranks Test for Median of Single Population

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The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...
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Microsoft Excel: Median, Quartile range, and Box Plots01:29

Microsoft Excel: Median, Quartile range, and Box Plots

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In Microsoft Excel, calculating the median, interquartile range, and creating box plots can help understand the distribution of your data.
Median and Quartile Range: The median is calculated using the formula `=MEDIAN(range)', which provides the middle value of your data set. Quartiles divide your data into four equal parts. To find the first and third quartiles, use ‘=QUARTILE(range, 1)' and ‘=QUARTILE(range, 3)', respectively. The interquartile range (IQR), which...
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Related Experiment Video

Updated: Feb 16, 2026

Functional and Physiological Methods of Evaluating Median Nerve Regeneration in the Rat
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A method to remove chattering alarms using median filters.

Yongkui Sun1, Wen Tan2, Tongwen Chen3

  • 1School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan, PR China; Department of Electrical & Computer Engineering, University of Alberta, Edmonton, Alberta, Canada.

ISA Transactions
|December 31, 2017
PubMed
Summary

This study reduces nuisance chattering alarms in industrial plants using median filters. The proposed method effectively minimizes false and missed alarms, enhancing alarm system reliability.

Keywords:
Alarm systemsChattering alarmsMedian filters

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Area of Science:

  • Industrial Automation
  • Signal Processing
  • Control Systems Engineering

Background:

  • Chattering alarms are a significant issue in industrial settings, leading to reduced system usability and a crisis of confidence in alarm systems.
  • Nuisance alarms degrade the effectiveness of critical safety and operational alerts.

Purpose of the Study:

  • To develop and validate a method for reducing chattering alarms in industrial plants.
  • To improve the reliability and usability of industrial alarm systems.

Main Methods:

  • The study proposes the use of median filters to address chattering alarms.
  • Two distinct rules for designing the median filter window size are formulated based on available data: one using process data for alarm probability and another using historical alarm data for chattering alarm reduction.
  • The first rule optimizes false alarm rate and missed alarm rate, while the second focuses on percentage reduction of chattering alarms.

Main Results:

  • Experimental results from industrial cases demonstrate the effectiveness of the proposed median filter approach.
  • The method successfully reduces the incidence of chattering alarms.

Conclusions:

  • Median filters provide an effective solution for mitigating chattering alarms in industrial environments.
  • The developed rules for filter design offer a practical approach to enhance alarm system performance and user trust.