A Smart Dual-Mode Calorimetric Flow Sensor

Abstract

A smart thermal flow sensor system is presented. It makes use of a novel heater control circuit which can automatically set the operating mode to either constant power or constant temperature difference. It overcomes the limitations of single-mode thermal flow sensors, such as temperature overshoots at low flow rates at constant power mode, or excessive power consumption at high flow rates at constant temperature difference mode. The system is especially useful for temperature sensitive and portable applications, such as respiratory monitoring for medical diagnostics. In this paper, detailed description of the sensor's design, implementation, and experimental validation are presented. The proposed dual-mode flow sensor achieves an overtemperature reduction up to 9.5% compared with thermal flow sensors operating in constant power mode alone, and a power reduction up to 13.6% compared with thermal flow sensors operating in constant temperature difference mode alone for the flow range of 0 to 50 slm while offering an improved overall sensitivity.

A Thermopile-Based Gas Flow Sensor with High Sensitivity for Noninvasive Respiration Monitoring

“…Conventionally, there are two types of thermal flow sensors, namely the thermistor flow sensors [ 16 , 17 , 18 ] and the thermopile flow sensors [ 19 , 20 ]. For the thermistor-based flow sensors, their fabrication process is relatively simple and low-cost, but complicated external circuits are usually required to convert resistance variation to voltage signals.…”

Wearable microfluidic sweat collection platform with a calorimetric flow rate sensor for realtime and long-term sweat rate measurements

“…The governing equation for thermal flow sensors' operation and heater's control is derived from King's Law [18]:…”

“…Using equation (18), with an approximate fluid mass of 10 mg, heat capacity of 0.480 J g −1 , and a ∆T = 22 K, (since the reference temp is 320 K and the reference temp drops to 298 K when fluid flows through the microchannel based from simulation), an empirical plot relating the amount of current needed to cause the change in temperature and the corresponding duration is generated (see figure 10). It can be seen that at shorter heating duration (t < 5 s), the amount of current needed to produce the target temperature is higher, and vice versa.…”

Utilization of Machine Learning Techniques in Hot‐Film Based Airflow Rate Sensors for Improving Flow Measurement

“…Additionally, moving structures such as cantilevers [9,10] and turbines [11,12] can be used to measure the flow rate. Various types of thermal flow sensors, including calorimetric, [13][14][15] time-of-flight, [16][17][18] and hot-wire/hot-film [19][20][21][22][23] sensors, can be used to measure the flow rate based on convective heat transfer caused by heaters and fluid flow. However, these conventional sensors require complex installation processes that depend on the flow channel geometry as well as expensive fabrication methods to create moving/heating components.…”