Sensor Calibration Techniques Research Articles

Calibration technique for airborne vibration sensors based on actuators

Addressing the challenge of in-situ calibration for onboard vibration sensors in aircraft installations, we propose an online calibration method based on actuators. Leveraging the inverse piezoelectric effect, we employ piezoelectric actuators mounted on the vibration sensors to calibrate vibration signals. Experimental results demonstrate that the influence of the actuator on the energy transfer of the measured sensor’s vibration signal during the calibration process can be negligible, meeting the calibration accuracy requirements of onboard vibration sensors. Through validation experiments, we determine the excitation coefficients of the actuators at different frequencies, subsequently obtaining the sensitivity of the vibration sensors equipped with actuators. The results reveal that within the frequency range, the relative error of sensitivity remains within ±3%, satisfying the relevant calibration requirements. Therefore, the actuator-based online calibration technique offers an efficient means of calibrating onboard vibration sensors, carrying significant practical value.

Particle tracking in snow avalanches with in situ calibrated inertial measurement units

Abstract In the course of an artificially triggered avalanche, a particle tracking procedure is combined with supplementary measurements, including Global Navigation Satellite System (GNSS) positioning, terrestrial laser scanning and Doppler radar measurements. Specifically, an intertial measurement unit is mounted inside a rigid sphere, which is placed in the avalanche track. The sphere is entrained by the moving snow, recording translational accelerations, angular velocities and the flux density of Earth's magnetic field. Based on the recorded data, we present a threefold analysis: (i) a qualitative data interpretation, identifying different particle motion phases which are associated with corresponding flow regimes, (ii) a quantitative time integration algorithm, determining the corresponding particle trajectory and associated velocities on the basis of standard sensor calibration, and (iii) an improved quantitative evaluation relying on a novel in situ sensor calibration technique, which is motivated by the limitations of the given dataset. The final results, i.e. the evolution of the angular orientation of the sensor unit, translational and rotational velocities and estimates of the sensor trajectory, are assessed with respect to their reliability and relevance for avalanche dynamics as well as for future design of experiments.

An Overview of Microrobotic Systems for Microforce Sensing

Considering microbotics, microforce sensing, their working environment, and their control architecture together, microrobotic force-sensing systems provide the potential to outperform traditional stand-alone approaches. Microrobotics is a unique way for humans to control interactions between a robot and micrometer-size samples by enabling the control of speeds, dynamics, approach angles, and localization of the contact in a highly versatile manner. Many highly integrated microforce sensors attempt to measure forces occurring during these interactions, which are highly difficult to predict because the forces strongly depend on many environmental and system parameters. This article discusses state-of-the-art microrobotic systems for microforce sensing, considering all of these factors. It starts by presenting the basic principles of microrobotic microforce sensing, robotics, and control. It then discusses the importance of microforce sensor calibration and active microforce-sensing techniques. Finally, it provides an overview of microrobotic microforce-sensing systems and applications, including both tethered and untethered microrobotic approaches.

A 12-bit single slope ADC with multi-step structure and ramp calibration technique for image sensors

This paper presents a novel multi-step single slope analog to digital converter (MS SS ADC). The proposed ADC splits the 12-bit conversion into 3 steps, including 1-bit half section decision, 4-bit coarse conversion, and finally 8-bit fine conversion with 1-bit redundancy. The conversion step is substantially reduced from conventional 4096 to 276. The linearity of the ADC is guaranteed by a stable common mode voltage of the comparator varying only within 31.25 mV. Moreover, two high-accuracy ramp calibration techniques are utilized to correct the current variation in the fine ramp and the slope error between the coarse and fine ramps. A hybrid comparator is utilized in the ADC to save power while maintaining the performance. The ADC is designed and simulated in 0.18 μm CMOS process with 7.5 μm width. The differential nonlinearity and integral nonlinearity of the proposed ADC are reduced from +0.3/-1 LSB and +3.1/-2.55 LSB to +0.3/-0.3 LSB and +1/-0.45 LSB at 61.7 kS/s sample rate by the calibrations.

A Quadrifocal Tensor SFM Photogrammetry Positioning and Calibration Technique for HOFS Aerial Sensors

Nowadays, the integration between photogrammetry and structure from motion (SFM) has become much closer, and many attempts have been made to combine the two approaches to realize the positioning, calibration, and 3D reconstruction of a large number of images. For the positioning and calibration of high oblique frame sweep (HOFS) aerial cameras, a quadrifocal tensor SFM photogrammetry technique is proposed to resolve the positioning and calibration task of such cameras. It adopts the quadrifocal tensor idea into the OpenMVG SFM pipeline to solve the complexity problem caused by the small single-viewing imaging area and the high image overlapping ratio. It also integrates the photogrammetry iteration idea into the OpenMVG SFM pipeline to enhance the positioning and calibration accuracy, which includes a coarse to fine three-stage Bundle Adjustment (BA) processing approach. In this paper, the overall workflow of the proposed technique was first introduced in detail, from feature extraction and image matching, relative rotation and translation estimation, global rotation and translation estimation, and the quadrifocal tensor model construction to the three-stage BA process and calibration. Then, experiments were carried out in the Zhengzhou area, implementing four types of adjustment methods. The results suggest that the proposed quadrifocal tensor SFM photogrammetry is suitable for large tilt frame sweep camera positioning and calibration without prior information on detailed camera intrinsic parameters and structure. The modifications made to the OpenMVG SFM pipeline enhanced the precision of image positioning and calibration and provided the precision level of professional photogrammetry software.

Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring.

With the emergence of Low-Cost Sensor (LCS) devices, measuring real-time data on a large scale has become a feasible alternative approach to more costly devices. Over the years, sensor technologies have evolved which has provided the opportunity to have diversity in LCS selection for the same task. However, this diversity in sensor types adds complexity to appropriate sensor selection for monitoring tasks. In addition, LCS devices are often associated with low confidence in terms of sensing accuracy because of the complexities in sensing principles and the interpretation of monitored data. From the data analytics point of view, data quality is a major concern as low-quality data more often leads to low confidence in the monitoring systems. Therefore, any applications on building monitoring systems using LCS devices need to focus on two main techniques: sensor selection and calibration to improve data quality. In this paper, data-driven techniques were presented for sensor calibration techniques. To validate our methodology and techniques, an air quality monitoring case study from the Bradford district, UK, as part of two European Union (EU) funded projects was used. For this case study, the candidate sensors were selected based on the literature and market availability. The candidate sensors were narrowed down into the selected sensors after analysing their consistency. To address data quality issues, four different calibration methods were compared to derive the best-suited calibration method for the LCS devices in our use case system. In the calibration, meteorological parameters temperature and humidity were used in addition to the observed readings. Moreover, we uniquely considered Absolute Humidity (AH) and Relative Humidity (RH) as part of the calibration process. To validate the result of experimentation, the Coefficient of Determination (R2), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) were compared for both AH and RH. The experimental results showed that calibration with AH has better performance as compared with RH. The experimental results showed the selection and calibration techniques that can be used in designing similar LCS based monitoring systems.

Optimal Control Method of Variable Air Volume Terminal Unit System

This study reviewed the existing studies on the types of variable air volume (VAV) terminal units, control and operation methods, prediction models, and sensor calibration methods. As a result of analyzing the existing research trends on the system type, characteristics, and control method of VAV terminal units studies such as theoretical verification and energy simulation were conducted to improve the existing control methods, reset the set value using a mathematical model, and add a monitoring sensor for the application of control methods. The mathematical model used in the study of VAV terminal unit control methods was used to derive set values for minimum air volume, supply temperature, ventilation requirements, and indoor comfort. The mathematical model has a limitation in collecting input information for professional knowledge and model development, and development of a building environment prediction model using a black box model is being studied. The VAV terminal unit system uses a sensor to control the device, and when an error occurs in the sensor, indoor comfort problems and energy waste occur. To solve this problem, sensor calibration techniques have been developed using statistical models, mathematical models, and Bayesian statistical models. The possibility of developing a method for calibrating the variable air volume terminal unit sensor using the prediction model was confirmed. In conclusion, the VAV terminal unit system is one of the most energy efficient systems. The energy saving potential of current VAV systems can still be improved through control methods, the use of predictive models, and sensor calibration methods.

Star Sensor Calibration Using Fine Guidance Sensor Information for Installation Errors

To correct installation errors of star sensors, we propose an error calibration method based on the measurement information from fine guidance sensors (FGS). This work established an extended Kalman filter model by using the measurement information of FGS as the observation to estimate position errors. Simulation experiments are presented to assess the effectiveness of the proposed star sensor calibration technique, and the results demonstrate the improved error estimation accuracy.

Datacenter Thermal Monitoring Without Blind Spots: FBG-Based Quasi-Distributed Sensing

Computing performance and hardware integrity are tightly linked to adequate thermal management in datacenters. In addition, a large share of its electricity bills comes from cooling systems, so there is a pressing need for enhanced thermal management systems. This paper proposes a fiber Bragg grating (FBG) quasi-distributed sensing device as an alternative to electronic sensors. The main focus is to demonstrate that a FBG-based solution allows thermal measurement at critical non-monitored regions (blind spots) within a server in an acquisition rate of 1 Hz, with thermal sensitivity of 8.757 pm/°C, a thermal resolution smaller than 1 °C and spatial resolution and multiplexing needed to monitoring diverse blind spots where there is virtually no room for adapting conventional sensors. In addition, we also monitor spots where there are already internal sensors next to them (referential spots), such as central processing unit (CPU) and graphics processing unit (GPU). As a result, a simple FBG sensor calibration technique is proposed using those referential spots. The technique proposed can be scaled out to monitor a large number of elements across large areas in a datacenter environment, since quasi-distributed FBG sensing signal can be transmitted over longer optical fibers than those employed in optical distributed temperature systems (DTS).

A Novel Background Calibration Technique for Microwave Radiometric Sensors in Indoor Applications

This letter presents a novel background calibration technique for microwave radiometers in indoor applications such as security sensing for static targets where unknown noise sources may add to background noise and degrade measurement accuracy. Such a background correction is important for absolute measurement of radiometric apparent temperature as opposed to relative measurement of contrast. The technique is validated by measuring the error in apparent temperature of hot water using a 23.55 GHz radiometer in an uncontrolled environment where the background noise is artificially increased using a diode-based noise source. The calibration technique reduced the prediction error introduced due to incorrect assumptions about the background by approximately 1 to 3 K.

CalibrationTalk: A Farming Sensor Failure Detection and Calibration Technique

Sensor failure detection and calibration is an important issue for Internet of Things applications. Many smart applications fail due to inaccurate data produced by their sensors. To solve this issue, we propose the CalibrationTalk mechanism. We use smart agriculture as an example to show how CalibrationTalk automatically fixes the sensing accuracy problems in commercial farm operations. Besides manufacturing variation, hardware malfunction and aging, sensing inaccuracy may be caused by soil erosion of rain or irrigation, which changes the positions and the angles of the sensors inserted in the soil. The above sensor failure problems can be detected by CalibrationTalk. In this article, we first extend our previous work to detect sensor failures. If the sensors become inaccurate due to aging or similar reasons, CalibrationTalk automatically calibrates the sensors in the farm fields. We conduct measurements and analytic modeling to investigate the performance of CalibrationTalk, which suggests that to detect a potential moisture sensor failure, it is appropriate to set the detection time as 30 min for moisture sensors. With this setup, true failure is detected while false detections rarely occur. For a detected sensor failure due to aging, CalibrationTalk can automatically build a calibration table. During the calibration table establishment period, the sensors still produce correct measured data and do not interfere with the normal operation of smart farming. The value of CalibrationTalk lies in its power of automation for sensor failure detection and calibration processes developed in this article.

Soil Structure and Texture Effects on the Precision of Soil Water Content Measurements with a Capacitance- Based Electromagnetic Sensor

HighlightsCapacitance-based electromagnetic soil moisture sensors were tested in disturbed and undisturbed soils.The uncertainty in estimation of soil water depth was lower using the undisturbed soil sample calibrations.The uncertainty in estimation of soil water depletion was lower than the uncertainty in volumetric water content.Undisturbed calibration of water depletion quantifies water demand with better precision and avoids over-watering.Abstract. The physical properties of soil, such as structure and texture, can affect the performance of an electromagnetic sensor in measuring soil water content. Historically, calibrations have been performed on repacked samples in the laboratory and on soils in the field, but little research has been done on laboratory calibrations with intact (undisturbed) soil cores. In this study, three replications each of disturbed and undisturbed soil samples were collected from two soil texture classes (Yutan silty clay loam and Fillmore silt loam) at a field site in eastern Nebraska to investigate the effects of soil structure and texture on the precision of a METER Group GS-1 capacitance-based sensor calibration. In addition, GS-1 sensors were installed in the field near the soil collection sites at three depths (0.15, 0.46, and 0.76 m). The soil moisture sensor had higher precision in the undisturbed laboratory setup, as the undisturbed calibration had a better correlation [slope closer to one, R2undisturbed (0.89) > R2disturbed (0.73)] than the disturbed calibrations for the Yutan and Fillmore texture classes, and the root mean square difference using the laboratory calibration (RMSDL) was higher for pooled disturbed samples (0.053 m3 m-3) in comparison to pooled undisturbed samples (0.023 m3 m-3). The uncertainty in determination of volumetric water content (?v) was higher using the factory calibration (RMSDF) in comparison to the laboratory calibration (RMSDL) for the different soil structures and texture classes. In general, the uncertainty in estimation of soil water depth was greater than the uncertainty in estimation of soil water depletion by the sensors installed in the field, and the uncertainties in estimation of depth and depletion were lower using the calibration developed from the undisturbed soil samples. The undisturbed calibration of soil water depletion would determine water demand with better precision and potentially avoid over-watering, offering relief from water shortages. Further investigation of sensor calibration techniques is required to enhance the applicability of soil moisture sensors for efficient irrigation management. Keywords: Calibration, Capacitance, Depletion, Irrigation, Precision, Sensor, Soil water content, Structure, Uncertainty.

The computational methods in the development of a novel multianalyte calibration technique for potentiometric integrated sensors systems

In recent years, integration and miniaturization of ion-selective electrodes (ISEs) have brought many benefits resulting in the possibility of simultaneous determination of the ions concentration in small volume samples. One of the key problems related to the preparation of potentiometric integrated sensors systems (PISSs) is a calibration procedure due to the necessity to calibrate each particular sensor separately. The main aim of the research was to develop a novel calibration method for PISSs fabricated with the use of an all-solid-state technology, which has been compared with other types of sensor calibration technique. The proposed algorithm concerns the method of calibration solutions composition determination for miniature ion-selective sensors before measuring in biological samples especially human saliva samples. This article also compares the parameters of ion-selective sensors for two types of PISSs, including ISEs based on gold (Au) and glassy carbon (GC) electrodes. In addition, a series of measurements was performed using PISS with Au-ISEs in samples of human saliva, which were preceded by different types of sensor calibration and compared with the results obtained with the clinical analyzer. Moreover, the effect of the viscosity of calibration solutions on the ISE parameters and the lifetime of the sensors were investigated.

Environment-Adaptive Calibration System for Outdoor Low-Cost Electrochemical Gas Sensors

To date, air pollution has caused over seven million deaths worldwide. Real-time monitoring is an efficient solution to prevent and mitigate air pollution. However, air quality monitoring networks are not currently dense enough to cover a large area because of the cost. With the development of low-cost electrochemical gas sensors, the current air quality monitoring network could be extended to a large area with a relatively high-resolution ratio. Nevertheless, the electrochemical gas sensors are not accurate enough compared to standard sensors if they are not carefully calibrated. Therefore, we proposed an environment-adaptive calibration (EAC) system dedicated to the implementation of a collaborative calibration technique for outdoor low-cost electrochemical gas sensors. The EAC system uses a new practical calibration algorithm operating on the Raptor IoT cloud platform that was developed as part of the H2020 Captor project. The system can identify the linear characteristics of gas sensors according to weather conditions, which is valuable prior knowledge for the calibration and the unique character of the EAC system. The outstanding performance of the EAC system is verified by the evaluation of a long-term measurement campaign, in which various metrics are considered, e.g., the goodness-of-fit, target diagram, and daily residuals.

Development and Analysis of Hybrid Thermoelectric Refrigerator Systems

Thermoelectric module (TEM) is a type of solid-state devices which has the capability to maintain the accuracy of small temperature variation application. In this study, a hybrid thermoelectric refrigerator system is introduced by utilizing TEMs; direct and air to air thermoelectric heat pump to cool down and maintain low temperature for vaccines storage. Two different materials which are aluminum and stainless steel are used as container in hybrid thermoelectric refrigerator (HTER) configuration to investigate the response of every system in transient and steady state mode. A proper temperature sensor calibration technique is implemented to make certain real time data acquisition of the systems are not affected very much from the noise generated. From step response analysis, it is indicated that HTER I (aluminum) has rapid settling time from transient to steady state than HTER II (stainless steel) since aluminum has better thermal conductivity as compared to stainless steel. It is found that HTER I is better in cooling capability with the same input current instead of HTER II which required a longer time to achieve steady state mode. Besides, in Pseudo Random Binary Sequence (PRBS) response analysis injected to both systems shows HTER I is very sensitive to current input as the sequence length of HTER I is shorter than HTER II. However both systems depict the varying temperature in the range of 4 oC due to differences in thermal conductivity of container.

SCAN

Urban air pollution monitoring with mobile, portable, low-cost sensors has attracted increasing research interest for their wide spatial coverage and affordable expenses to the general public. However, low-cost air quality sensors not only drift over time but also suffer from cross-sensitivities and dependency on meteorological effects. Therefore calibration of measurements from low-cost sensors is indispensable to guarantee data accuracy and consistency to be fit for quantitative studies on air pollution. In this work we propose sensor array network calibration (SCAN), a multi-hop calibration technique for dependent low-cost sensors. SCAN is applicable to sets of co-located, heterogeneous sensors, known as sensor arrays, to compensate for cross-sensitivities and dependencies on meteorological influences. SCAN minimizes error accumulation over multiple hops of sensor arrays, which is unattainable with existing multi-hop calibration techniques. We formulate SCAN as a novel constrained least-squares regression and provide a closed-form expression of its regression parameters. We theoretically prove that SCAN is free from regression dilution even in presence of measurement noise. In-depth simulations demonstrate that SCAN outperforms various calibration techniques. Evaluations on two real-world low-cost air pollution sensor datasets comprising 66 million samples collected over three years show that SCAN yields 16% to 60% lower error than state-of-the-art calibration techniques.

Cryogenic system for precise calibration of temperature sensors

A calibration technique for cryogenic temperature sensors is proposed and implemented. The experimental setup is based on the helium cryogenerator, providing calibration of the temperature sensors of various types in wide temperature range, including cryogenic band (25-100K). A condensation thermometer with hydrogen, neon, argon and xenon as working gases is used as a reference sensor. The experimental setup was successfully used for precise (0.1K precision) calibration of platinum resistive temperature detectors (Pt-100) for international nuclear physics experiments MuSun and PolFusion. The setup can also be used for calibration of temperature sensors of the other types.

Pressure Sensor Calibration for Measuring Stud-player Impacts

In rugby union, laceration injuries can occur from players stamping on opponents in the ruck. To measure the stud-skin interaction during stamping movements, pressure sensors can be used. Pressure sensor calibration techniques have highlighted the need to perform calibrations using appropriate impact dynamics. A pilot study with seven rugby players informed the expected peak forces and loading rates of rugby stamps. Subsequently, a custom calibration procedure was developed, using a drop hammer and force platform to replicate the experimentally observed forces and loading rates. The conventional calibration of the pressure sensor system, supplied by the manufacturer, overestimated total force by 132%. The method described in this paper resulted in a mean error of 7.5%. This study describes a simple and effective calibration procedure for using pressure sensors when measuring the peak force from stud-player impacts. The method has potential to be used as an improved calibration protocol when the expected peak force range of the measured event is between 1800 and 3000N. The calibrated pressure sensors will be used to obtain kinetic data from stamping events in the ruck in rugby union.

A simple sensor calibration technique for estimating the 3D pose of endoscopic instruments.

The aim of this study was to describe a simple and easy-to-use calibration method that is able to estimate the pose (tip position and orientation) of a rigid endoscopic instrument with respect to an electromagnetic tracking device attached to the handle. A two-step calibration protocol was developed. First, the orientation of the instrument shaft is derived by performing a 360° rotation of the instrument around its shaft using a firmly positioned surgical trocar. Second, the 3D position of the instrument tip is obtained by allowing the tip to come in contact with a planar surface. The results indicate submillimeter accuracy in the estimation of the tooltip position, and subdegree accuracy in the estimation of the shaft orientation, both with respect to a known reference frame. The assets of the proposed method are also highlighted by illustrating an indicative application in the field of augmented reality simulation. The proposed method is simple, inexpensive, does not require employment of special calibration frames, and has potential applications not only in training systems but also in the operating room.

Sensors for Robotics 2015

Robot is currently one of the exciting and fast developing technologies changing the life of human being. It has been widely applied in lots of areas such as industry, agriculture, medicine, transportation, social service, military, space exploration, and undersea exploiting. Increasing attention by robot researchers has been paid to the robot sensor, as a key component of the robot. During the last decade, much effort has been done to develop robot sensors for robot perception, robot control, autonomous robot, human-robot interaction, and so forth. In spite of the large and increasing interest and promising applications, robot sensor design is a significant challenging, which is involved in not only sensor materials, structure design, manufacturing process, and calibration technique, but also signal processing, data fusion, and pattern recognition. For instance, remarkable examples of tactile sensors and systems have been proposed; however, their ability to address specific applications and their extension to other fields such as medical instrumentation, prosthetic devices, and biomechanics test is questionable. This special issue aims at exhibiting the latest research achievements, ideas, and advances in robot sensors.