• Become a member
  • Log In
The Institution of Electronics
  • Home
  • About us
    • Our Objectives
    • Our History
    • Governance of the Institution
  • The Electron Magazine
    • 2024
      • 2024 – Winter
      • 2024 – Spring
      • 2024 – Summer
      • 2024 – Autumn
    • 2025
      • 2025 – Winter
      • 2025 – Spring
      • 2025 – Summer
      • 2025 – Autumn
    • 2026
      • 2026 – Winter
  • Members
    • Membership Grades and Fees
    • Members’ Resources
      • The Electron Newsletter
      • The Archives
  • Education and Projects
    • National Electronics Competition
    • Student Members’ Projects
    • Arkwright Engineering Scholarships
  • News
  • Contact Us
  • Menu Menu
Uncategorised

Proper function linearizes a hot transistor anemometer with less than 0.2 % error

A recent Design Idea presents a circuit to measure an airflow rate up to 2000 fpm using two transistors in a Darlington configuration. One transistor works as a self-heated thermal sensor and the other one compensates for ambient temperature variations. The circuit is smart and simple; however, the output voltage depends on the input flow rate in a very nonlinear fashion. The paper presents two hardware options to linearize the sensor response, which reduce nonlinearity to about 10-12% of the maximum flow rate. 

Wow the engineering world with your unique design: Design Ideas Submission Guide

Modern microcontrollers offer significant calculation power, sometimes at a very low price, so it is worth trying to find a calculation solution to the nonlinearity problem.

Before we start, let’s recall the principle of linearization: the circuit or the calculation formula that will process the output signal of the sensor circuit must generate the inverse function of the sensor response. For example, if the sensor response is a log function, the response of the linearizing section must be exponential.

The work started with getting 46 discrete points of the sensor response (see Figure 4 in the reference paper). The discretion step is small at the beginning where the curve rises fast and gets bigger as the curve becomes more and more flat. Attempts to fit the flow rate versus voltage response with a piecewise approximation or cubic splines can reduce linearity error to 1-2% at the cost of bulky formulas. It would be much better if the whole curve is covered by a single smooth function.

Several functions of different complexity were tested. The best results were achieved with a composite function of the form:

where N is the number to be generated by the microcontroller and Vs is the output voltage of the sensor circuit. The presence of four coefficients, A to D, provides a lot of flexibility to fit the desired set of points.

The Solver tool of MS Excel found the proper values of the unknown coefficients:

A = 10525.4, B = -4.49563, C = 9103.05 and D = -1.36567.

As Figure 1 shows, passing the sensor voltage through this function provides a highly linear relation between the number N to be displayed and the flow rate. Figure 2 presents the deviation between the discrete points of the response and the best fit linear equation. The error is within the ±2.5 fpm range, which is 0.125 % of the maximum flow rate. This is 80 times better than the hardware solutions in the reference paper. An important feature is that the error will affect only the last digit in the displayed number.

Figure 1 The calculation approach provides a highly linear, 1:1 relation between the displayed number and the airflow rate.

 Figure 2 Close insight reveals a very small nonlinearity of the overall response.

In real applications, the error may not be that small due to errors in the A-to-D conversion, limited size of numbers and rounding errors during the calculations; however, it will be still much better than the hardware solutions.

If the proposed function looks too complicated to you, feel free to try any other function you may wish. A good tutorial on how to use the Solver tool is available here. Uncheck the “Make Unconstrained Variables Non-negative” box, so the unknown coefficients can get negative values.

–Jordan Dimitrov is an electrical engineer & PhD with 30 years of experience. Currently he teaches electrical and electronics courses at a Toronto community college.

 Related Content

Nonlinearities of Darlington airflow sensor and VFC compensate each other
Manage your measurement errors
Linearized portable anemometer with thermostated Darlington pair
Transistor linearly digitizes airflow
Self-heated Darlington transistor pair comprises new air flow sensor
Precision synchronous detection amplifier facilitates low voltage measurements
RMS stands for: Remember, RMS measurements are slippery
Antilog converter linearizes carbon dioxide sensor

<!–
googletag.cmd.push(function() { googletag.display(‘div-gpt-ad-native’); });
–>

The post Proper function linearizes a hot transistor anemometer with less than 0.2 % error appeared first on EDN.

18 December 2023
http://institutionofelectronics.ac.uk/wp-content/uploads/2022/12/IOE_LOGO.png 0 0 http://institutionofelectronics.ac.uk/wp-content/uploads/2022/12/IOE_LOGO.png 2023-12-18 14:59:502023-12-18 14:59:50Proper function linearizes a hot transistor anemometer with less than 0.2 % error

Latest news

  • Four-channel USB-UART IC boosts server management13 August 2026 - 05:08
  • eFuse speeds overcurrent detection13 August 2026 - 05:08
  • Memory platform tackles AI bottlenecks13 August 2026 - 05:08
  • 6.5-kV SiC MOSFET reaches 8-kV blocking13 August 2026 - 05:08
  • Made by Google 2026: This limited silicon-supply situation really sucks13 August 2026 - 05:08
  • Cheap and cheerful LMC555 RC PWM pulse generator12 August 2026 - 13:56
  • Record high wafer shipments. Can fabs keep pace?12 August 2026 - 07:51
  • Analog uncertainty-aware design: How it replaces Monte Carlo with certifiable yield intelligence11 August 2026 - 16:31
  • Automotive low side output switch architecture suitable for 8 to 48 volt buses and beyond11 August 2026 - 13:26
  • Inference 2.0: How enterprise AI is reshaping AI system architectures11 August 2026 - 07:19
IOE LOGO 2

Become a member

click here

Become a member

click here

Become a subscriber

click here

Become a sponsor

click here

© Copyright - The Institution of Electronics | Website by WHD Solutions
  • Link to LinkedIn
  • Link to Facebook
  • Link to X
Link to: Application of machine learning in power management systems Link to: Application of machine learning in power management systems Application of machine learning in power management systems Link to: Analog of a thyristor with a controlled switching threshold Link to: Analog of a thyristor with a controlled switching threshold Analog of a thyristor with a controlled switching threshold
Scroll to top Scroll to top Scroll to top