Response time testing of temperature sensors using loop current step response method

2013 ◽  
Author(s):  
H. M. Hashemian
Keyword(s):  
Response Time ◽  
Temperature Sensors ◽  
Step Response ◽  
Loop Current ◽  
Current Step ◽  
Response Method

Untersuchung des dynamischen Verhaltens von Berührungsthermometern unter realen Bedingungen

2018 ◽  
Vol 85 (2) ◽  
pp. 119-127
Author(s):  
Andreas Brethauer ◽  
Thomas Fröhlich ◽  
Elmar Engels
Keyword(s):  
Step Response ◽  
Loop Current ◽  
Current Step ◽  
Response Test

Zusammenfassung Zur Bestimmung des dynamischen Verhaltens von Berührungsthermometern existieren standardisierte Messvorrichtungen. Die auf diese Weise ermittelten Thermometerkennwerte ermöglichen den Vergleich unterschiedlicher Thermometer. Mit dem Ansprechverhalten unter realen Einbaubedingungen haben die so ermittelten Kennwerte jedoch oft wenig zu tun. Im vorliegenden Beitrag wird das dynamische Verhalten unterschiedlicher Berührungsthermometer in unterschiedlichen Einbausituationen miteinander verglichen. Dabei kommen ein Temperatursprung an der Thermometer-Außenseite, sowie ein sogenannter Loop-Current-Step-Response-Test (LCSR-Test) zum Einsatz. Der LCSR-Test kann hier gerade unter Einbaubedingungen eine Aussage über das Ansprechverhalten eines Thermometers liefern.

scholarly journals Outdoor Air Temperature Measurement: A Semi-Empirical Model to Characterize Shelter Performance

Climate ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 26
Author(s):  
Jérémy Bernard ◽  
Pascal Kéravec ◽  
Benjamin Morille ◽  
Erwan Bocher ◽  
Marjorie Musy ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Response Time ◽  
Air Temperature ◽  
Empirical Model ◽  
Regression Coefficient ◽  
Radiation Sensitivity ◽  
Temperature Sensors ◽  
Outdoor Air ◽  
The One ◽  
Semi Empirical

Shelters used to protect air temperature sensors from solar radiation induce a measurement error. This work presents a semi-empirical model based on meteorological variables to evaluate this error. The model equation is based on the analytical solution of a simplified energy balance performed on a naturally ventilated shelter. Two main physical error causes are identified from this equation: one is due to the shelter response time and the other is due to its solar radiation sensitivity. A shelter intercomparison measurement campaign performed by the World Meteorological Organization (WMO) is used to perform a non-linear regression of the model coefficients. The regression coefficient values obtained for each shelter are found to be consistent with their expected physical behavior. They are then used to simply classify shelters according to their response time and radiation sensitivity characteristics. Finally, the ability of the model to estimate the temperature error within a given shelter is assessed and compared to the one of two existing models (proposed by Cheng and by Nakamura). For low-response-time shelters, our results reduce the root mean square error by about 15% (0.07 K) on average when compared with other compensation schemes.

scholarly journals Modeling and Implementation of TEG-Based Energy Harvesting System for Steam Sterilization Surveillance Sensor Node

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6338
Author(s):  
Mateusz Daniol ◽  
Lukas Boehler ◽  
Ryszard Sroka ◽  
Anton Keller
Keyword(s):  
Power Generation ◽  
Thermal Gradient ◽  
Step Response ◽  
Steam Sterilization ◽  
Storage Unit ◽  
Ultra Low Power ◽  
Sensor Applications ◽  
Physical Prototype ◽  
Energy Harvesting System ◽  
Response Method

The aim of this work is a proof of concept, that medical Internet of Things (IoT) sterilization surveillance sensors can be powered by using the heat during a steam sterilization procedure. Hereby, the focus was on the use of thermo-electrical generators (TEG) to generate enough power for an ultra-low-power sensor application. Power generation requirement of the sensor was 1.6 mW over the single sterilization cycle. The thermal gradient across the TEG has been achieved using a highly efficient aerogel-foam-based thermal insulation, shielding a heat storage unit (HSU), connected to one side of the TEG. The evaluation of the developed system was carried out with thermal and electrical simulations based on the parameters extracted from the TEG manufacturer’s datasheet. The developed model has been validated with a real prototype using the thermal step response method. It was important for the authors to focus on rapid-prototyping and using off-the-shelf devices and materials. Based on comparison with the physical prototype, the SPICE model was adjusted. With a thermal gradient of 12 °C, the simulated model generated over 2 mW of power. The results show that a significant power generation with this system is possible and usable for sensor applications in medial IoT.

Turbocharger Dynamic Analysis Using First Order System Step Response

2009 ◽  
Author(s):  
Giuliano Gardolinski Venson ◽  
Jose´ Eduardo Mautone Barros
Keyword(s):  
Phase Shift ◽  
Response Time ◽  
Combustion Chamber ◽  
Rotational Speed ◽  
Moment Of Inertia ◽  
Step Test ◽  
Step Response ◽  
Order System ◽  
Signal Frequency ◽  
First Order

This work presents the dynamic modeling of an automotive turbocharger in a hot gas test stand. The objective is to develop a methodology to determine the main turbocharger dynamic properties as moment of inertia, response time, static gain constant, frequency gain amplitude and phase shift. The turbocharger used is the Master Power APL-240 set. The moment of inertia is obtained through the deceleration curve from an instantaneous fuel cut-off in the combustion chamber. The response time and static gain constant, as well the frequency gain amplitude and phase shift curves in function of a signal frequency, are obtained through a step variation. The turbocharger is modeled as a first order system. It is also presented a turbocharger sine excitation by the combustion chamber, generating a rotational speed sine signal output that simulates an engine intermittent acceleration. The rotational speed signal frequency gain and phase shift are compared to the values obtained in the step curves. The rotational speed frequency gain amplitude and phase shift modeled through the step test presents deviation of 16% and 13%, respectively, from the values from sine test.

Comparison of Buck–Boost and Ćuk Converters Based on Time Domain Response

2018 ◽  
Vol 27 (14) ◽  
pp. 1850222
Author(s):  
J. Leema Rose ◽  
B. Sankaragomathi
Keyword(s):  
Pid Controller ◽  
Closed Loop ◽  
State Equation ◽  
Power Converter ◽  
Open Loop ◽  
Step Response ◽  
State Equations ◽  
Loop Control ◽  
Time Domain Response ◽  
Response Method

This paper presents the design and modeling of power electronic converters such as buck–boost and Ćuk operated under continuous conduction mode (CCM). The open-loop behavior of buck–boost and Ćuk converters needs modeling and simulation using modeled equations. The closed-loop control of these converters has a propositional–integral–derivative (PID) controller. PID controller parameters are obtained from Ziegler–Nichols step response method. These converters can be analyzed using the state equation. The MATLAB/SIMULINK tool is used for simulation of those state equations. Ćuk and buck–boost converters are designed and analyzed. The mathematical model of power Converter for simulation has been carried out using SIMULINK with/without any Sim Power System Elements. The open- and closed-loop results are compared.

scholarly journals Multi-channel Precision Bias Source for Experiments on Quantum dots

2021 ◽  
Author(s):  
yumei tang ◽  
kefu liu ◽  
haixing sun
Keyword(s):  
Quantum Dots ◽  
Response Time ◽  
High Precision ◽  
Dynamic Range ◽  
Step Response ◽  
Precise Control ◽  
Device Application ◽  
Short Time

To realize precise control of the quantum dots (Qdots) device, multi-channel precision bias source plays the key role. In this paper, the 16-channel high precision bias source with 18-bit resolution for Qdots device was designed. The prototype was made and its performance was tested. The short time fluctuations can reach 50μV. The step response time is less than 3μs. The resolution, stability, linearity and dynamic range of the bias source exhibits good performance. What's more, the bias source can be controlled locally and online. The results show that it is one effective and feasible topology for experiments in Qdots device application.

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