Abstract:A sensor interface circuit based on impulse radio pulse width modulation (IR-PWM) is presented for low power and high throughput wireless data acquisition systems (wDAQ) with extreme size and power constraints. Two triple-slope analog-to-time converters (ATC) convert two analog signals, each up to 5 MHz in bandwidth, into PWM signals, and an impulse radio (IR) transmitted (Tx) with an all-digital power amplifier (PA) combines them while preserving the timing information by transmitting impulses at the PWM risi… Show more
“…where, T and R are the measured values, and T and R are the exact values. Figure 12 shows the error for measured temperature according to Equation (6). Although the error of resistance values in simulations and experiments was large, as shown in Figure 10, the error was less than 1.5%.…”
Section: Simulations and Experimentsmentioning
confidence: 93%
“…When T 0 = 298.15 K, R 0 = 1000 Ω, and B 0 = 3950. The error in measuring the temperature can be derived from the resistance value, as in Equation (6).…”
Section: Simulations and Experimentsmentioning
confidence: 99%
“…In the era of rapid development of the Internet of Things (IoT), data acquisition systems have been widely applied in all walks of life [1][2][3], including biomedicine, engineering construction, and industrial manufacturing [4][5][6]. In the process of data acquisition, both information and power need to be transmitted through wires.…”
This paper presents a passive wireless measurement system based on wireless power transfer (WPT) technology. It does not require separate information and power transmission circuits. The data receiver only needs to send a short signal to the data collector through WPT, and then the information of the measured environment can be obtained by analyzing the feedback signal from the data collector. Three concepts are included in this system, namely (1) the constant oscillation period of oscillation attenuation waveforms; (2) the characteristics of inductive coupling WPT; and (3) the relationship between sensitive resistances and environmental parameters. It is very suitable for measuring the parameters in an internal or closed space. The data collector is small in size and simple in structure, and no power is needed. It has stable performance after implantation and can be used permanently. Results obtained from simulations and experiments are included. They verify the measurement process and measurement results meet the requirements of passive wireless measurement, and the measurement error is less than 1.5%.
“…where, T and R are the measured values, and T and R are the exact values. Figure 12 shows the error for measured temperature according to Equation (6). Although the error of resistance values in simulations and experiments was large, as shown in Figure 10, the error was less than 1.5%.…”
Section: Simulations and Experimentsmentioning
confidence: 93%
“…When T 0 = 298.15 K, R 0 = 1000 Ω, and B 0 = 3950. The error in measuring the temperature can be derived from the resistance value, as in Equation (6).…”
Section: Simulations and Experimentsmentioning
confidence: 99%
“…In the era of rapid development of the Internet of Things (IoT), data acquisition systems have been widely applied in all walks of life [1][2][3], including biomedicine, engineering construction, and industrial manufacturing [4][5][6]. In the process of data acquisition, both information and power need to be transmitted through wires.…”
This paper presents a passive wireless measurement system based on wireless power transfer (WPT) technology. It does not require separate information and power transmission circuits. The data receiver only needs to send a short signal to the data collector through WPT, and then the information of the measured environment can be obtained by analyzing the feedback signal from the data collector. Three concepts are included in this system, namely (1) the constant oscillation period of oscillation attenuation waveforms; (2) the characteristics of inductive coupling WPT; and (3) the relationship between sensitive resistances and environmental parameters. It is very suitable for measuring the parameters in an internal or closed space. The data collector is small in size and simple in structure, and no power is needed. It has stable performance after implantation and can be used permanently. Results obtained from simulations and experiments are included. They verify the measurement process and measurement results meet the requirements of passive wireless measurement, and the measurement error is less than 1.5%.
“…For that reason, different quasi-digital converters have been reported in literature including resistance-toduty cycle, resistance-to-frequency, and resistance-to period, as they are simpler topologies, offering a wide dynamic range and a simplified interface to digital systems (e.g. microprocessors) [40]- [44].…”
With rising hazardous organic vapours in the environment, the detection of volatile organic vapour compounds (VOCs) is becoming important. To this end, this paper presents a conductive droplet-based disposable sensor. Unlike conventional sensors, the droplet system is easily replaceable and is capable of detecting multiple vapours based on surface tension gradient. The chemiresistive sensor presented here is fabricated on 2.5 µm thick ultra-flexible graphene oxide-chitosan (GOC) with Pt electrodes having 60 µm gap. The electrostatic interaction and strong hydrogen bonds between GO and polysaccharide groups in chitosan provide tunable hydrophobicity and stability to the droplet. With a conductive droplet of ∼10 µL of aq. NaCl as an active sensing material dispensed between the Pt electrodes, it was observed that the droplet showed 14-21% change in resistance in the presence of VOCs. A read-out circuit was also designed to get the data from the droplet sensor. The response time for the presented sensor (3-4 seconds) is significantly better than its solid-state sensor counterparts. With attractive features such as disposability, affordability and fast response the presented sensor will find applications in industrial environments, laboratories, health centres, and biomedical devices.
“…This results in large and complex configurations and linearization techniques must be applied due to the intrinsic limitation in the dynamic range [2][3][4]. In contrast, quasi-digital converters, i.e., resistance-to-frequency [5,6], -period [7,8] or -duty-cycle [9] converters, are preferred if the resistance variations are very large. This converters not only provide a wider dynamic range but also simplify interfacing to digital systems, as no analog-to-digital converters (ADCs) are required [10,11].…”
The signal from a resistive sensor must be converted into a digital signal to be compatible with a computer through an interface circuit. Resistance-to-Period converter, used as interface, is preferred if the resistance variations are very large. This paper presents the structure of an interface circuit for resistive sensors that is highly robust to component and power supply variations. Robustness is achieved by using the ratiometric approach, thus complex circuits or highly accurate voltage references are not necessary. To validate the proposed approach, a prototype was implemented using discrete components. Measurements were carried out considering a variation of ±35% in the single supply voltage and a range from 1 k Ω to 1 M Ω .
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