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Related Concept Videos

Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
Calibration Curves: Correlation Coefficient01:10

Calibration Curves: Correlation Coefficient

In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the other increases, and...
Glassware Calibration01:11

Glassware Calibration

Accurate calibration of glassware, such as volumetric flasks, pipettes, and burettes, is essential to ensure accurate measurements in the analytical laboratory. Calibration helps maintain consistency across measurements and prevents errors arising from inaccurate volumes.
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Flame Photometry: Overview01:02

Flame Photometry: Overview

Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
Flame Photometry: Lab01:16

Flame Photometry: Lab

In a flame photometer, when a solution like potassium chloride is aspirated into the flame, the solvent evaporates, leaving behind dehydrated salt. This salt dissociates into free gaseous atoms in their ground state. Some of these atoms absorb energy from the flame, leading to their excitation. The excited atoms return to the ground state, emitting photons at characteristic wavelengths. Because only electronic transitions are involved, the resulting emission lines are very narrow. The intensity...

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Related Experiment Video

Updated: May 13, 2026

In Situ Monitoring of the Accelerated Performance Degradation of Solar Cells and Modules: A Case Study for Cu(In,Ga)Se2 Solar Cells
09:19

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Published on: October 3, 2018

Error modeling and calibration for encoded sun sensors.

Qiaoyun Fan1, Guangjun Zhang, Jian Li

  • 1School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China.

Sensors (Basel, Switzerland)
|March 9, 2013
PubMed
Summary

This study analyzes encoded sun sensor (ESS) errors, developing a compensation model and calibration method. The new method improves ESS measurement accuracy threefold within a 60-degree incident angle range.

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Area of Science:

  • Aerospace Engineering
  • Optical Sensing
  • Metrology

Background:

  • Encoded Sun Sensors (ESS) are crucial for spacecraft attitude determination.
  • ESS performance can be degraded by internal errors and calibration inaccuracies.
  • Accurate sun angle measurements are vital for mission success.

Purpose of the Study:

  • To analyze and simulate error factors in ESS.
  • To develop an ESS error compensation model.
  • To propose a calibration method for improving ESS accuracy.

Main Methods:

  • Analysis and simulation of ESS error factors.
  • Establishment of an ESS error compensation model addressing structural and fine-code algorithm errors.
  • Introduction of installation deviation as an external parameter for accurate model calibration.

Main Results:

  • An ESS error compensation model was successfully established.
  • A novel calibration method incorporating installation deviation was proposed and validated.
  • ESS measurement accuracy improved by an average factor of three within ±60° incident angles.

Conclusions:

  • The developed compensation model and calibration method significantly enhance ESS accuracy.
  • Accurate calibration, considering installation deviations, is critical for reliable ESS performance.
  • The findings contribute to improved attitude determination in space missions.