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Superior to the traditional infrared temperature sensing architecture including infrared sensor and thermistor, we propose a novel sensing approach based on a single thermopile sensor with dual modes modulation. A switching and sensing circuit is proposed and realized with a chopper amplifier AD8551 and p-channel MOSFET (PMOS) for switching between...
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... difference of the two radiations is net heat radiation, and the target temperature can be estimated. This study used a black body radiation cavity to generate a target temperature and placed the sensor 4 cm in front of the cavity, as shown in Figure 1a. ...
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... sensor of proposed thermopile with TO-5 package is connected to a dual mode switching circuit. In this circuit, the power is supplied and regulated by a source circuit containing a low- dropout regulator (LDO), and the switching circuit is implemented by a PMOS.The output signal of thermopile sensor is delivered to an amplifier AD8551 with low offset and an Analog-to-Digital Converter (ADC) 24-bit, 3-channel AD7799 which transfers it into the digital signal, as shown in Figure 1b. The mathematical model of thermal radiation measurements is expressed as Equations (1) to (3) below, which reveal the relationship of infrared radiation to ambient temperature for infrared temperature sensing. ...
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... thermal radiation measurement, the target temperature is set from 30 to 80 °C. In Figure 10a, the sensor output voltage rises as the target temperature increases, and its sensitivity is about 0.5 mV/°C for target temperature change. After switching to the effective thermistor sensing mode, the voltage of effective thermistor is acquired and analyzed, and the drop of voltage range is about 0.6 mV during the calibration, as shown in Figure 10b. ...
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... Figure 10a, the sensor output voltage rises as the target temperature increases, and its sensitivity is about 0.5 mV/°C for target temperature change. After switching to the effective thermistor sensing mode, the voltage of effective thermistor is acquired and analyzed, and the drop of voltage range is about 0.6 mV during the calibration, as shown in Figure 10b. ...
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... temperature calibration and ambient temperature compensation are necessary for the measurement of sensor. Figure 11a show the calibration curve of the effective thermistor, and the ambient temperature range is setup from 25 to 80 °C with a step of 5 °C. From Figure 11a, the sensitivity is derived as −0.4 mV/°C for ambient temperature change. ...
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... 11a show the calibration curve of the effective thermistor, and the ambient temperature range is setup from 25 to 80 °C with a step of 5 °C. From Figure 11a, the sensitivity is derived as −0.4 mV/°C for ambient temperature change. Then, the relationship between the change of ambient temperature ΔTa and the change of thermopile output voltage ΔVb is measured and analyzed, as shown in Figure 11b. ...
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... Figure 11a, the sensitivity is derived as −0.4 mV/°C for ambient temperature change. Then, the relationship between the change of ambient temperature ΔTa and the change of thermopile output voltage ΔVb is measured and analyzed, as shown in Figure 11b. ...
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... we adjust the standard blackbody with temperature from about 30 °C to 80 °C and measure the thermopile output voltage under a stable environment. The calibration is proceeded under dual mode switching, measurement of the target temperature is achieved and a calibration curve after the ambient temperature compensation is shown in Figure 12. The curve of data is fitted with 4th order of polynomial, which is in agreement of Stefan-Boltzmann's law. ...
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... analysis of errors generated during the measurement and calculation comes from the instability of ambient temperature compensation. The maximum error of ambient temperature compensation from curve fitting in Figure 11b is calculated about 0.158 mV for the worst case ΔTa = 53 °C, and it will deduce the maximum error of target temperature with 0.17 °C. Finally, for the measurement of target temperature from 30 °C to 80 °C and the ambient temperature drift ΔTa = 1.8 °C, the overall error is within ±0.14 °C. ...
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Citations
... The solution to this problem is the use of thermopile sensors. They are matrices of thermocouples, measuring 8x8 pixels [3]. In order to use such data, they need to be interpolated and scaled. ...
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... Therefore, how to effectively improve the accuracy and reliability of NCIT equipment is a very valuable research topic [14][15][16][17][18][19][20][21]. Many scholars and engineers have adopted different methods to solve these problem, specially the ambient temperature compensation, which can be divided into hardware and algorithm schemes. ...
... Many scholars and engineers have adopted different methods to solve these problem, specially the ambient temperature compensation, which can be divided into hardware and algorithm schemes. Shen et al [14] proposed a novel dual-mode modulation infrared temperature sensing method based on a switching circuit composed of an operational amplifier AD8551 and a p-channel MOSFET, therefore, only a single thermopile sensor is needed to realize infrared radiation and ambient temperature sensing. After ambient temperature compensation, the error of infrared temperature measurement is less than 0.14 ℃. ...
The non-contact infrared thermometer (NCIT) is an important basic tool for fever screening and self-health monitoring. However, it is susceptible to the thermal shock when working in a low temperature environment, which will cause a time-consuming and inaccurate human body temperature measurements. To overcome the effects of thermal shock, a hybrid temperature compensation method combining hardware and algorithm is proposed. Firstly, the principle of infrared temperature measurement is described and the influence of thermal shock on infrared thermometer is analyzed. Then, the hybrid temperature compensation scheme is constructed by mounting a heating ring on the infrared sensor shell, and using the proportional integral derivative (PID) algorithm and the pulse width modulation (PWM) technology to control it heating. In this way, the internal ambient temperature of infrared sensor can be raised rapidly closing to the external ambient temperature, and the stable outputs of the infrared sensor are also accelerated. Finally, some experiments are carried out in a laboratory. The results show that the proposed method can quickly and accurately measure the temperature of standard black body when the ambient temperatures are 5 , 15 and 25 Celsius respectively, the measurement error is only 0.2 Celsius , and the measurement time is less than 2 seconds. This study would be beneficial to improve performance of NCIT, especially the infrared ear thermometer.
... Thermopile vacuum sensors, based on the Seebeck effect, are fully compatible with CMOS processes, thereby enabling high yield production with minimal post-MEMS processing [1][2][3][4][13][14][15][16][17]. Due to the multi-physics of MEMS devices, it is convenient to use a finite element method for modeling and simulation. ...
When using a MEMS sensor to measure the vacuum of a medium, the transition flow between the viscous flow and molar flow is usually used to describe the gas convection due to the physical principle, which is difficult to study through analysis and simulation. In this study, the description of gas flow under different pressures in a CMOS-MEMS vacuum sensors has been incorporated into a new behavioral ANSYS model. The proposed model was built and the characteristic parameters in the model were obtained based on a CMOS-MEMS thermopile patterned with circular symmetry and an embedded heater as a heat source. It contains a characteristic length to describe the effective distance of heat dissipation to the silicon substrate, and the corresponding transition pressure to describe the symmetrical phenomenon of gas heat conduction. The macro-model is based on the description of the physical characteristics of heat transfer and the characteristic parameters of the CMOS-MEMS vacuum sensor. The characteristic length of 49 μm and the corresponding transition pressure of 2396 mTorr for the thermoelectric-type vacuum sensor were extracted and verified successfully. The results show that the average error for the prediction of vacuum sensing by the macro-model we proposed is about 1.11%. This approach provides more applications for vacuum analysis. It can reduce the complexity of simulation and analysis and provide better simulation effects, including gas conduction mechanisms.
