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Related Concept Videos

Temperature Measurement Sites01:14

Temperature Measurement Sites

1.8K
A thermometer measures body temperature. The common sites for measuring body temperature are the oral cavity, axillary region, temporal artery, and skin surface, such as the forehead, abdomen, and axilla. True core body temperature is assessed in the rectum, tympanic membrane, pulmonary artery, esophagus, and urinary bladder.
Oral: When assessing oral temperature, the thermometer tip should be placed under the tongue in the posterior sublingual pocket. It offers accurate readings and can be...
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Instrument Calibration01:12

Instrument Calibration

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Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
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Equipments Used to Measure Body Temperature01:13

Equipments Used to Measure Body Temperature

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Body temperature can be assessed using various devices and measured in Celsius or Fahrenheit.
Glass-bulb Thermometer:
Glass-bulb thermometers are hollow glass tubes with a bulb tip containing liquid such as ethanol or mercury. Historically, glass bulb mercury thermometers were the standard device to measure body temperature. Today, mercury thermometers are prohibited in many countries due to the hazardous effects of mercury and the risk of exposure if the glass bulb breaks. In general,...
1.0K
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

1.4K
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...
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Thermometers and Temperature Scales01:22

Thermometers and Temperature Scales

5.5K
Any physical property that depends consistently and reproducibly on temperature can be used as the basis of a thermometer. For example, volume increases with temperature for most substances. This property is the basis for the common alcohol thermometer and the original mercury thermometers. Other properties used to measure temperature include electrical resistance, color, and the emission of infrared radiation.
As many physical properties depend on temperature, the variety of thermometers is...
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Distance Corrections01:15

Distance Corrections

50
To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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Related Experiment Video

Updated: Jul 16, 2025

Manufacturing Simple and Inexpensive Soil Surface Temperature and Gravimetric Water Content Sensors
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Machine-Learning-Based Calibration of Temperature Sensors.

Ce Liu1,2, Chunyuan Zhao2, Yubo Wang3

  • 1College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
Summary

Artificial neural network (ANN) models enhance temperature sensor accuracy for industrial applications. ANNs offer superior calibration compared to linear and polynomial regression, but require careful sample design to prevent overfitting.

Keywords:
accuracyartificial neural network (ANN)calibrationlinear regressionoverfittingpolynomial regressionstabilitytemperature sensor

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Area of Science:

  • Instrumentation and Measurement
  • Computational Science
  • Industrial Engineering

Background:

  • Accurate temperature measurement is critical for industrial production quality and safety.
  • Existing temperature sensors require precise calibration for optimal performance.
  • Traditional calibration methods may lack the accuracy needed for demanding applications.

Purpose of the Study:

  • To investigate the effectiveness of artificial neural network (ANN) models for calibrating temperature sensors.
  • To compare ANN calibration performance against traditional linear and polynomial regression techniques.
  • To identify key factors for successful ANN-based temperature sensor calibration.

Main Methods:

  • Collected temperature data from standard sensors across diverse environmental conditions.
  • Developed and applied an artificial neural network (ANN) model for sensor calibration.
  • Compared calibration accuracy of ANN, linear regression, and polynomial regression models.

Main Results:

  • ANN model calibration significantly improved temperature sensor accuracy.
  • ANN models demonstrated superior calibration performance over linear and polynomial regression.
  • Overfitting risks were identified, linked to small sample sizes or noisy data.

Conclusions:

  • Artificial neural networks provide a more accurate calibration method for temperature sensors.
  • Careful design of training samples and model parameter adjustment are crucial for effective ANN calibration.
  • This study offers valuable technical support for industrial temperature measurement applications.