Today, the sensing devices play an important role for various system automation and monitoring of different physical and chemical parameters. Nonlinearity is an important long-time issue for most of the sensors, so to compensate nonlinearity, various linearization schemes are reported in the literature. The accuracy of linearization schemes depends on the type and the nonlinearity value of the sensor output. Since it is difficult to find an exact polynomial equation or other functions to represent the response curve; it gives more error when the measurement parameter is determined from the inverse approximation functions. As many sensors are used for different applications, the linearized characteristics will simplify the design, calibration, and accuracy of the measurement. This paper presents a review of different methods applied to linearize sensor characteristics reported in the literature. Due to availability of high-performance analog devices, analog methods are still popular among many researchers. However, due to the advancement of IC technologies, hardware implementation of the software methods can be done easily with reduced time, cost, and more accuracy, so the digital methods combined with software techniques perform the job with better flexibility and efficiency.

/pdf/linearization-of-the-sensors-characteristics-a-review-4l71ua71m2.pdf

Linearization of the sensors characteristics: a review

For current microelectronic integrated systems, the design methodology involves different steps that end up in the full system simulation by means of electrical and physical models prior to its manufacture. However, the higher the circuit complexity, the more time is required to complete these simulations, jeopardizing the convergence of the numerical methods and, hence, meaning that the reliability of the results are not guaranteed. This paper shows the use of a high-level tool based on Matlab to simulate the operation of an artificial neural network implemented in a mixed analog-digital CMOS process, intended for sensor calibration purposes. The proposed standard tool enables modification of the neural model architecture to adapt its characteristics to those of the electronic system, resulting in accurate behavioral models that predict the complete microelectronic IC system behavior under different operation conditions before its physical implementation with a simple, time-efficient, and reliable solution.

High-Level Modeling and Simulation Tool for Sensor Conditioning Circuit Based on Artificial Neural Networks

In the contact type capacitive liquid level sensors, when an electrode with the insulating film is immersed in polar/ionic medium, it shows constant phase behavior at metal–insulator interface due to the formation of the double layer. This double layer effect is frequently modeled by a pure capacitor but its capacitance value depends on signal frequency. Therefore, when such a sensor is excited by sinusoidal ac, the conducting liquid level measurement suffers from the error due to the fluctuation of input signal frequency. This is because the excitation frequency applied from the source meter may fluctuate. This important issue is rarely discussed for the capacitive level sensors. In addition, the design and realization of the capacitive level sensor require special arrangements for the minimization of parasitic earth capacitance, offset capacitance, and the capacitances due to leads and contact electrodes. In this paper, we propose a novel constant phase impedance sensor for the measurement of conducting liquid levels in the range of 0–4 cm for the first time. The phase angle of the device changes due to a change in the liquid level. Two important characteristics parameters of the sensor are the constant phase angle for a certain frequency range and the fractional order in the range of 0–1. Some important features of the sensor are significant sensitivity (2.1 ∘ /cm, probe 1) due to small change in conducting liquid, stable output due to fluctuation of input frequency, and the fabrication of the sensor is very simple and inexpensive. The device is finally interfaced to a phase detection circuit to convert the phase angle into a voltage signal.

A constant phase impedance sensor for measuring conducting liquid level.

This paper addresses the challenges of selecting a suitable method for negative temperature coefficient (NTC) thermistor-based temperature measurement in electronic devices. Although measurement accuracy is of great importance, the temperature calculation time represents an even greater challenge since it is inherently constrained by the control algorithm executed in the microcontroller (MCU). Firstly, a simple signal conditioning circuit with the NTC thermistor is introduced, resulting in a temperature-dependent voltage UT being connected to the MCU’s analog input. Next, a simulation-based approximation of the actual temperature vs. voltage curve is derived, resulting in four temperature notations: for a look-up table principle, polynomial approximation, B equation and Steinhart–Hart equation. Within the simulation results, the expected temperature error of individual methods is calculated, whereas in the experimental part, performed on a DC/DC converter prototype, required prework and available MCU resources are evaluated. In terms of expected accuracy, the look-up table and the Steinhart–Hart equation offer superior results over the polynomial approximation and B equation, especially in the nominal temperature range of the NTC thermistor. However, in terms of required prework, the look-up table is inferior compared to the Steinhart–Hart equation, despite the latter having far more complex mathematical functions, affecting the overall MCU algorithm execution time significantly.

Algorithm Execution Time and Accuracy of NTC Thermistor-Based Temperature Measurements in Time-Critical Applications

NTC thermistors are frequently used low in cost temperature sensors which provide some of the most desirable sensing features. However, due to the nonlinear static transfer function their sensitivity decreases with temperature increase, causing lower measurement accuracy in some regions of the measurement range. This paper proposes a method for NTC thermistor nonlinearity compensation using aWheatstone bridge and a novel dual-stage single-flash piecewise-linear ADC. Both conversion stages are performed using the same flash ADC of a novel design based on a reduced number of comparators employed. In this manner, simpler design, lower production costs, higher compactness and lower power consumption of the linearizing ADC, are achieved. The proposed linearizing method is tested on the Vishay NTCLE413E2103F520L thermistor, in the range from 0◦C to 100◦C, and the obtained results confirmed the effectiveness of the method in measurement accuracy improvement: when the flash ADC of 10-bit resolution is employed the accuracy obtained is 7.4747 · 10−5◦C.

NTC thermistor nonlinearity compensation using wheatstone bridge and novel dual-stage single-flash piecewise-linear ADC

To obtain the solutions to the problem of linearization of the sensor characteristics is a matter of investigations for a long time. This paper presents a new and simple piecewise linearizing circuit to compensate the nonlinearity of highly nonlinear sensor. It is having a mixed signal conditioning circuit, employing a 2-bit flash ADC, a ( 4 × 1 ) multiplexer and the Op amp-based signal conditioning units. The circuit was initially simulated using SPICE software and then hardware implemented for linearizing the nonlinear response characteristic of two sensors. One of the sensors is a graphene oxide capacitive humidity sensor with nearly 46% nonlinearity and the other is a thermistor-based temperature sensor with 16.4 % nonlinearity. The humidity sensor is fabricated and characterized to measure humidity in the range of 2–85% RH. The maximum nonlinearity of the humidity and temperature sensors of the hardware implemented circuit after compensation was 1% and 1.5 % respectively. The circuit is simple and requires few hardware components for implementation and applicable for any nonlinear sensor. The circuit is CMOS compatible for ASIC implementation.

Durga Nand Mahaseth

Papers

An efficient signal conditioning circuit to piecewise linearizing the response characteristic of highly nonlinear sensors