Capacitive Sensor Signal Research Articles

Processing of capacitive sensor signal profile for enhancing gestures detection

Processing of capacitive sensor signal profile for enhancing gestures detection

Simultaneous detection of the shuttling motion of liquid metal droplets in channels under alternating pressure and capacitive sensor signals

Implementing a signal-switching mechanism for the selective use of integrated sensors and actuators plays a crucial role in streamlining the functionality of miniaturized devices. Here, a liquid metal droplet (LMD)-based signal-switching mechanism is introduced to achieve such functionality. Pressure modulation with a 100-μm spatial resolution enabled precise control of the position of the LMDs within a channel. After integrating the channel with asymmetrically structured electrodes, the effect of the shuttle-like movement of LMD on the temporal changes in the overall capacitance was investigated. Consequently, analysis of the capacitive peaks revealed the directional movement of the LMDs, enabling estimation of the position of the LMDs without direct observation. In addition, we achieved successful signal extraction from the capacitive sensor that was linked to the activated electrodes, thereby enabling selective data retrieval. The proposed signal-switching mechanism method achieved a detection accuracy of ~0.1 pF. The sensor’s ability to simultaneously detect the LMD position and generate a signal underscores its significant potential for multiplexing in multisensing systems, particularly in concealed environments, such as in vivo settings.

A Pseudo-Differential Capacitive MEMS Accelerometer Analog Front-End Design

Based on the current design and application of the chip and the research status at home and abroad, we proposed a silicon micro-accelerometer analog front-end integrated circuit with high resolution and wide capacitance application range by using SMIC 0.18μm CMOS technology. The circuit is composed of a capacitive readout circuit, a demodulator, and a low-pass filter. To detect the weak capacitive signal, the capacitor readout circuit of this paper adopts the continuous-time voltage mode charge amplifier structure and combines with the signal modulation technology and the optimization of the MOS transistor size to achieve low noise and high resolution. With the application of the signal modulation technology, the low-frequency capacitance sensor signal is shifted from 2-12 kHz to high-frequency 800 kHz. The signal modulation technology modulates the low-frequency capacitive sensor signal of 2~12 kHz at the high frequency of 800 kHz, and the signal is converted into voltage through the capacitive readout circuit. The simulation results show that the designed analog front-end circuit can convert the accelerometer capacitance signal with the frequency of 2~12 kHz, the dynamic capacitance peak is 0.108 pF, and the static capacitance is 10 pF into the expected voltage signal. In addition, the output noise can be as low as 556 nV/√Hz in the capacitive frequency range of the accelerometer, which meets the requirement of 2.5 aF capacitive resolution. Therefore, the silicon micro-accelerometer analog front-end circuit designed in this paper has the characteristics of a wide capacitor application range, low noise, and high resolution, and can be widely used.

A Model-Based Analysis of Capacitive Flow Metering for Pneumatic Conveying Systems: A Comparison between Calibration-Based and Tomographic Approaches.

Pneumatic conveying is a standard transportation technique for bulk materials in various industrial fields. Flow metering is crucial for the efficient and reliable operation of such systems and for process control. Capacitive measurement systems are often proposed for this application. In this method, electrodes are placed on the conveyor systems transport line and capacitive signals are sensed. The design of the sensor with regard to the arrangement and the number of electrodes as well as the evaluation of the capacitive sensor signals can be divided into two categories. Calibration-based flow meters use regression methods for signal processing, which are parametrized from calibration measurements on test rigs. Their performance is limited by the extend of the calibration measurements. Electrical capacitance tomography based flow meters use model-based signal processing techniques to obtain estimates about the spatial material distribution within the sensor. In contrast to their calibration-based counterparts, this approach requires more effort with respect to modeling and instrumentation, as typically a larger number of measurement signals has to be acquired. In this work we present a comparative analysis of the two approaches, which is based on measurement experiments and a holistic system model for flow metering. For the model-based analysis Monte Carlo simulations are conducted, where randomly generated pneumatic conveying flow patterns are simulated to analyze the sensor and algorithm behavior. The results demonstrate the potential benefit of electrical capacitance tomography based flow meters over a calibration-based instrument design.

Algorithms for Processing Measuring Signals in the Integrating Solid-State Wave Gyroscope

Different variants of algorithms for processing the internal signals of the measuring device of integrating solid-state wave gyroscopes are synthesized. The main attention is paid to the consideration of subtle factors affecting the accuracy of calculation of gyroscope output signals and measurement signals of internal circuits to ensure their effective operation. For this purpose, different models of capacitive sensor signals in the gyroscope measuring device and the measured structure of standing waves in its resonator are preliminarily considered. The traditional aggregation of sensor signals into measuring device signals is described. First, variants of algorithms for capacitive direct-current operating measuring devices are systematized and thoroughly analyzed. They are divided into algorithms with tuning for periodicity of resonant oscillations and without tuning for periodicity. Variants of calculations differing in accuracy are presented for: the angle of the operating standing wave, proportional to the measured rate of the gyroscope base rotation; the amplitude of the operating quadrature standing wave for the internal circuit of its assigned value maintenance; the amplitude of the quadrature standing wave for the internal circuit of its suppression; the frequency of the operating standing wave for tuning of the excitation system of resonator oscillations and for implementation of the digital quadrature coherent demodulator of the measuring device. It is shown that in the majority of practical applications algorithms with tuning to periodicity of resonant oscillations are more preferable from the point of view of the computational complexity. And computationally labor-intensive algorithms without periodicity tuning are intended for measuring increased angular velocities with the reduced time of "freezing" of measured parameters. Further the given algorithms for the direct-current measuring device are generalized on algorithms of processing of measuring signals when operating with the alternating current. The variants of computational algorithms reduction to the algorithms previously synthesized for the direct current are described. They mainly use demodulation of AC voltage signals, including digital processing of modulated signals using a high-speed analog-to-digital converter. In addition, algorithms for information extraction from AC measuring device signals with demodulation at the combined frequency of modulated signals are synthesized. The different variants of single-band demodulation of measurement signals and also algorithm of double-band demodulation of measuring device signals with the extended list of measured quantities are considered. The choice of the necessary algorithm depends on the requirements to the measured angular velocities, on the constructive implementation of the gyroscope measuring device and on the choice of technical characteristics of its components.

The optimization algorithm for blind processing of high frequency signal of capacitive sensor

At present, the high frequency signal processing algorithm of capacitive sensor based on RBF has the problems of poor filtering effect and high level of signal detection and poor quality of signal separation. In this paper, an optimization algorithm for blind processing of high frequency signal of capacitive sensor is proposed. Based on the gradient method, and the calculation way of improved variance gradient estimation, the gradient of square single- error sample is taken as the estimation of mean square error to filter the capacitive sensor signal, and adjust the filtering step by adjusting the threshold, which can enhance the filtering effect of the sensor signal; The detection threshold is calculated by determining the false alarm probability. The decision condition is used to detect the target signal and get the high accuracy sensor signal. The initialization separation matrix is set according to the number of observation signals, and the correlation matrix of the source signal can be calculated, so as to achieve the efficient separation of high frequency signals. The experiment shows that the algorithm can effectively solve the problems existing in the current signal processing algorithm, and it is reliable.

Instrumented urethral catheter and its ex vivo validation in a sheep urethra

This paper designs and fabricates an instrumented catheter for instantaneous measurement of distributed urethral pressure profiles. Since the catheter enables a new type of urological measurement, a process for accurate ex vivo validation of the catheter is developed. A flexible sensor strip is first fabricated with nine pressure sensors and integrated electronic pads for an associated sensor IC chip. The flexible sensor strip and associated IC chip are assembled on a 7 Fr Foley catheter. A sheep bladder and urethra are extracted and used in an ex vivo set up for verification of the developed instrumented catheter. The bladder-urethra are suspended in a test rig and pressure cuffs placed to apply known static and dynamic pressures around the urethra. A significant challenge in the performance of the sensor system is the presence of parasitics that introduce large bias and drift errors in the capacitive sensor signals. An algorithm based on use of reference parasitic transducers is used to compensate for the parasitics. Extensive experimental results verify that the developed compensation method works effectively. Results on pressure variation profiles circumferentially around the urethra and longitudinally along the urethra are presented. The developed instrumented catheter will be useful in improved urodynamics to more accurately diagnose the source of urinary incontinence in patients.

Mixed-grained CMOS field programmable analog array for smart sensory applications

The drive towards shorter design cycles for analog integrated circuits has given impetus to the development of Field Programmable Analog Arrays (FPAAs), which are the analogue counterparts of Field Programmable Gate Arrays (FPGAs). In this paper, we present a new design methodology which using FPAA as a powerful analog front-end processing platform in the smart sensory microsystem. The proposed FPAA contains 16 homogeneous mixed-grained Configurable Analog Blocks (CABs) which house a variety of processing elements especially the proposed fine-grained Core Configurable Amplifiers (CCAs). The high flexible CABs allow the FPAA operating in both continuous-time and discrete-time approaches suitable to support variety of sensors. To reduce the nonideal parasitic effects and save area, the fat-tree interconnection network is adopted in this FPAA. The functionality of this FPAA is demonstrated through embedding of voltage and capacitive sensor signal readout circuits and a configurable band pass filter. The minimal detectable voltage and capacitor achieves 38 uV and 8.3 aF respectively within 100 Hz sensor bandwidth. The power consumption comparison of CCA in three applications shows that the FPAA has high power efficiency. And the simulation results also show that the FPAA has good tolerance with wide PVT variations.

Very Low Power Supply Dependence ROIC for Capacitive Sensing Platforms

This paper presents a very low power consumption read out integrated circuit (ROIC) for conditioning and acquiring capacitive sensor signals for a frequency based converter platform with programmable resolution. The platform consists of a temperature compensated voltage reference circuit (bandgap) coupled to a low power capacitance to frequency converter (CtoF). It interfaces to a frequency processing architecture with high efficient frequency-to-code converters. A controlled compensation of the channel length modulation effect and the suppression of mobility dependence reduce the consumption of the ROIC down to 26 μA at half power supply. Furthermore, the temperature dependent coefficient achieved is only 16 ppm/ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> C. In addition, the coupled compensated bandgap reference circuit compensates the power supply dependence of the CtoF, ensuring an output frequency completely independent of the power supply.

Mapping of horizontal refrigerant two-phase flow patterns based on clustering of capacitive sensor signals

A capacitive void fraction sensor was developed to study the objectivity in flow pattern mapping of horizontal refrigerant two-phase flow in macroscale tubes. Sensor signals were gathered with R410A and R134a in a smooth tube with an inner diameter of 8 mm at a saturation temperature of 15 °C in the mass velocity range of 200–500 kg/m 2 s and vapour quality range from 0 to 1 in steps of 0.025. A visual classification based on high speed camera images is made for comparison reasons. A statistical analysis of the sensor signals shows that the average, the variance and a high frequency contribution parameter are suitable for flow regime classification into slug flow, intermittent flow and annular flow by using the fuzzy c-means clustering algorithm. This soft-clustering algorithm predicts the slug/intermittent flow transition very well compared to our visual observations. The intermittent/annular flow transition is found at slightly higher vapour qualities for R410A compared to the prediction of Barbieri et al. (2008) [20]. An excellent agreement was obtained with R134a. This intermittent/annular flow transition is very gradual. A probability approach can therefore better describe such a transition. The membership grades of the cluster algorithm can be interpreted as flow regime probabilities. Probabilistic flow pattern maps are presented for R410A and R134a in an 8 mm ID tube.

Tracking Control of a Nanopositioner Using Complementary Sensors

Piezoelectric tube actuators are widely used in atomic force and scanning tunneling microscopy (STM) for nanoscale positioning. There has been a consistent effort to increase the scan speed of these actuators using feedback control techniques. A feedback controller requires a measurement of the scanner's deflection, which is often provided by a capacitive sensor. Such measurements are corrupted by sensor noise, typically in the order of 20 pm/ radicHz rms. Over a bandwidth of 10 kHz, this translates into an rms noise of 2 nm, clearly inadequate for applications that require subnanometer positioning accuracy, e.g., STM. In this paper, we illustrate how the strain voltage induced in a free electrode of the scanner can be used as an additional displacement signal. The noise level corresponding to the strain signal is about three orders of magnitude less than that of a capacitive sensor, making it an ideal choice for nanopositioning applications. However, it cannot be used for dc and low-frequency measurements. A two-sensor-based controller is designed to use the capacitive sensor signal at low frequencies, and the strain displacement signal at high frequencies. By limiting the capacitive sensor feedback loop bandwidth to less than 100 Hz, the rms value of the noise is reduced to well below 1 nm. For almost the same noise level, the two-sensor-based control structure achieves a closed-loop bandwidth of more than three times that of the single-sensor-based controller.

Simple and direct calculation of capacitive sensor sensitivity map

PurposeThe purpose of this paper is to introduce a rapid method for calculating capacitive sensor signal variations for any small permittivity or electrode modifications at any position in space.Design/methodology/approachWhen a capacitive sensor is probing its surrounding, the modification of the permittivity, the displacement or the deformation of one or more electrodes induce a signal variation which depends on the position of the modification. Seeing that modification as a small perturbation and using Gauss identity, it is possible to find integral expressions of the sensor sensitivity map.FindingsCapacitive sensor sensitivity map expressions depend only on the perturbation to measure, on the electric field before the perturbation, and on a sensitivity field which is the electric field produced by the sensor when the measuring electrode is held to 1 V while the others, except the floating ones, are grounded. The sensitivity field is a kind of Green's function for the capacitive sensor. The knowledge of the electric and sensitivity fields makes it possible to obtain the whole sensor sensitivity map at once without requiring time consuming parametric calculations.Originality/valueThe sensitivity field calculation provides a simple and direct view of the capacitive sensor capabilities. That should improve capacitive sensor design.

Tuning sensitivity and selectivity of complementary metal oxide semiconductor-based capacitive chemical microsensors.

New details on selectivity and sensitivity of fully integrated CMOS-based capacitive chemical microsensor systems are revealed. These microsystems have been developed to detect volatile organics in ambient air and rely on polymeric sensitive layers. The sensitivity and selectivity changes induced by thickness variation of the sensitive polymer layer allow for tuning of the layer parameters to achieve desired sensor features. Cross-sensitivity to interfering agents can be drastically reduced, as is shown for two important cases: (a). rendering the capacitive sensor insensitive to a low-dielectric-constant analyte (lower than that of the polymer) and (b). reducing the influence of a high-dielectric-constant analyte, such as water, on the sensor response. The second case is of vital importance for capacitive sensors, since water is omnipresent and evokes large capacitive sensor signals. The thickness-induced selectivity is explained as a combination of dielectric constant change and swelling and has been confirmed by measurements. Experimentally determined sensitivities qualitatively and quantitatively coincide with the calculated values implying understanding of the sensing mechanism.