Proposed Calibration Process Research Articles

Water distribution system calibration using the Finite Element Method coupled to a Genetic Algorithm

Water distribution systems (WDS) are a fundamental part of the infrastructure in our cities, for this reason increasingly capable numerical models have been developed in recent years to allow hydraulic systems be analyzed in great detail. Calibration process let get accurate and reliable information for those involved in design, operation, construction and maintenance of public WDS. In this study a calibration process is proposed using a Genetic Algorithms (GA) methodology with real number coding coupled to the Finite Element Method as hydraulic simulator GA-FEMH. The method proposed was applied to two calibration cases; one reported in literature and a real network.The results show that the proposed calibration process is reliable, and the WDS model can represent real conditions of the network according to the regulations that international organizations such as AWWA and WAA recommend. Moreover high correlation values were obtained after the calibration process, with values of R2 higher than 95 % for pressure and flow. Likewise, the FEM can be an alternative to use it as a hydraulic simulator due to its rapid convergence and its ease of integrating hydraulic accessories.

In Situ Drift Monitoring and Calibration of Field-Deployed Potentiometric Sensors Using Temperature Supervision.

Potentiometric ion-selective electrodes (ISEs) have broad applications in personalized healthcare, smart agriculture, oil/gas exploration, and environmental monitoring. However, high-precision potentiometric sensing is difficult with field-deployed sensors due to time-dependent voltage drift and the need for frequent calibration. In the laboratory setting, these issues are resolved by repeated calibration by measuring the voltage response at multiple standard solutions at a constant temperature. For field-deployed sensors, it is difficult to frequently interrupt operation and recalibrate with standard solutions. Moreover, the constant surrounding temperature constraint imposed by the traditional calibration process makes it unsuitable for temperature-varying field use. To address the challenges of traditional calibration for field-deployed sensors, in this study, we propose a novel in situ calibration approach in which we use natural/external temperature variation in the field to obtain the time-varying calibration parameters, without having to relocate the sensors or use any complex system. We also develop a temperature-supervised monitoring method to detect the drift of the sensor during operation. Collectively, the temperature-based drift monitoring and in situ calibration methods allow us to monitor the drift of sensors and correct them periodically to achieve high-precision sensing. We demonstrate our approach in three testbeds: (1) under controlled temperature variation in the lab, (2) under natural temperature variation in a greenhouse, and (3) in the field to monitor nitrate activity of an agricultural site. In the laboratory study, we validate that the calibration parameters of printed nitrate ISEs can be reproduced by our proposed calibration process; therefore, it can serve as an alternative to traditional calibration processes. In the greenhouse, we show the use of natural temperature variation to calibrate the sensors and detect the drift in a fixed concentration nitrate solution. Finally, we demonstrate the use of the method to monitor the nitrate activity of an agricultural field within 10% of laboratory-based measurements (i.e., a sensitivity of 0.03 mM) for a period of 22 days. The findings highlight the prospect of temperature-based calibration and drift monitoring for high-precision sensing with field-deployed ISEs.

Interactive 3D touch and gesture capable holographic light field display with automatic registration between user and content

AbstractThis paper presents an interactive three‐dimensional (3D) touch and gesture user interface that utilizes a light‐field display and a 3D sensor. In contrast to conventional gesture interfaces, in which usually the image space and gesture space are separated, a user can directly interact with the 3D image in this interface system. To achieve this trait, the 3D registration between the sensor and display coordinate systems is necessary. In this study, we propose a method to automatically match the position of the reconstructed 3D image with the position of the hand of the user based on scattered light detection. The proposed calibration process is automatic and enables self‐calibration during practical operation without laborious measurement work. The method allows us to use the gesture detection capabilities of the leap motion controller to develop an interface where content and gesture positions match. We show some examples of 3D touch and gesture interactions in which the gesture position and the generated content match on a light field display.

On the Calibration of an Optical, High-Speed, Multiphase Microfluidic Sensor With Droplet Counting Applications in Lab-on-PCB Devices

The integration of microfluidics and droplet-based systems has led to platforms capable of characterizing multiple phases inside microchannels which can be an asset for many industries. Furthermore, recent developments on Lab-on-a-PCB devices focus to meet design specifications such as the ASSURED criteria (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable to end-users). However, most of these systems still present external equipment dependencies, complex setup and manufacturing processes, low reproducibility, along reduced information regarding calibration processes for ASSURED-based sensors. In this work, we developed a rapid and fully integrated calibration process for optical droplet-based Lab-on-PCB devices by means of an interfacial distance constant called <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> , to obtain reliable and wide spectrum droplet detection and characterization results. To test the proposed calibration process, a low-cost optical droplet sensor was built using commonly available electronics components, consisting only of a fluid channel between a Light-Emitting Diode (LED) and a Light Dependent Resistor (LDR), which voltage variation is measured and processed with an Arduino Uno. After the proposed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> calibration of the platform, we were able to characterize different multiphase flow properties such as velocity, flow rate, droplet lengths, and volume for velocities up to 1000 droplets per second with the Mean Relative Errors (MRE) ranging from 2.4% up to 17%. The lowest MRE value was obtained using a two-phase flow system for flow from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$20 \mu \text{L}$ </tex-math></inline-formula> /min up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$425 \mu \text{L}$ </tex-math></inline-formula> /min. In contrast, the highest MRE value we report was found for a three-phase flow system for droplets at <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$250 \mu \text{L}$ </tex-math></inline-formula> /min.

Closed-Loop Kinematic Calibration of Robots Using a Six-Point Measuring Device

The low absolute positioning accuracy of robots has limited their applications for many precision tasks. Although the robot accuracy can be improved through kinematic calibration, traditional calibration approaches need either expensive external measurement devices or tedious manual intervention. To overcome these issues, this work proposes a closed-loop kinematic calibration method for robots using a six-point measuring device. This device consists of six displacement sensors to determine the pose of a gauge block as a reference workpiece mounted on the robot end-effector. A comprehensive error model is derived to calibrate the kinematic parameters including the Denavit-Hartenberg parameters of the robot geometry and the pose of the robot base. Then, the Levenberg-Marquard algorithm is adopted to identify these parameters. An experimental study has been conducted on a UR10 robot, combining a CMM to verify the calibration results. It is found that the maximum and average distance errors of the robot movement could be significantly decreased from over 5.60 mm and 2.50 mm to approximately 0.50 mm and 0.30 mm, respectively. Benefited from the fact that only six displacement sensors are used, the proposed method is cost effective. Also, the proposed calibration process can be completed without tedious manual teaching and thus easy to achieve autonomous calibration.

A novel combination of Mycielski–Markov, regime switching and jump diffusion models for solar energy

With renewable energy sources growing, solar power generation is becoming ever more popular around the world, so forecasting and scenario analysis of Solar Photovoltaic production is beneficial for grid operators and investors. In this paper, we introduce a novel combination of a Mycielski–Markov model, standard regime switching, and jump diffusion models to generate 1-minute Global Horizontal Irradiance time series over any time scale. It can simulate different scenarios of solar irradiance in the future after being trained on empirical data. We verify our model using statistical tests to compare our simulations with those from an observed time-series in Mauritius. The resulting model is able to generate simulations retaining the statistical properties of the data. Further, we find the proposed calibration process to be robust, and identified that splitting the day into 16 periods to be perfect balance to counter overfitting. The proposed model has the potential to better understand the effects of including large scale Solar Photovoltaic generation into an energy network, value future investments, or even allow for a cost–benefit analysis of subsidies.

Reliability-based assessment and calibration of standards for the lateral vibration of pedestrian bridges

Ensuring vibrations remain tolerable to occupants is central to the serviceability limit state (SLS) design of lightweight pedestrian bridges. In general, pedestrians tend to be more sensitive to lateral bridge vibrations compared to vertical vibrations, which underscores the importance of serviceability limit state (SLS) design in the lateral direction. Significant uncertainties associated with the pedestrian loading and bridge behaviour motivate the need to treat serviceability design provisions from a reliability standpoint. This paper is a first attempt towards such an assessment and code calibration of SLS provisions applicable to the lateral direction in the existing major pedestrian bridge design guidelines (ISO 10137, Eurocode 5 and SÉTRA). For this purpose, this study adopts a reliability-based framework, which accounts for the uncertainties arising from the pedestrian loading, perceptions of vibration by pedestrians, and structural damping. Furthermore, SLS design generally considers commonly occurring design traffic densities only. However, several historical lateral vibration serviceability failures of pedestrian bridges have occurred under infrequent loading events. Hence, this paper also incorporates infrequent traffic event (load case) in the reliability assessment and calibration of the design guidelines. Results show that metal truss-type pedestrian bridges under design and infrequent traffic events need to be designed to a higher reliability level (through calibration) than currently achieved by these provisions under the design event. Adopting traffic density and frequency-dependent acceleration limits can mitigate overdesigns resulting from the calibration exercise. The desired reliability index required to achieve minimum acceptable performance of the designs under both the design and infrequent events is estimated iteratively in the proposed procedure, followed by the calculation of design calibration factors. This study shows that the calibration of some design provisions (e.g., SÉTRA) depends on amplitude-dependent damping values, while this is not the case with other provisions. This dependency can be attributed to differences in the form of the limit state function. Finally, it is shown that the proposed calibration process achieves sufficient and consistent reliability across all bridge classes under design and infrequent traffic events in the lateral direction, while ensuring economic designs using traffic density and frequency-based comfort limits.

An extreme value theory based approach for calibration of microsimulation models for safety analysis

There is an increasing interest in using microsimulation models for traffic safety evaluations and several calibration procedures were proposed for the simulation models to obtain a high correlation between the simulated and field-measured conflicts. However, since the ultimate goal of safety studies is to reduce crashes, the simulation model needs to be calibrated to ensure an accurate prediction of crashes. The objective of this study is to propose an innovative calibration approach for microsimulation models using the extreme value theory (EVT) approach. The EVT approach was shown to connect non-crash events to crashes, providing reasonable crash estimates from traffic conflicts. The goal of the proposed calibration process is to produce an extreme value distribution of simulated conflicts that matches the one of field-measured conflicts. A Genetic algorithm is utilized to obtain VISSIM model parameters that can achieve this goal. Traffic video data collected from two approaches at a signalized intersection in Surrey, Canada were used as case studies. Automated traffic conflicts analysis techniques were used to extract field-measured conflicts. Simulated conflicts were extracted from vehicle trajectories from VISSIM using the surrogate safety assessment model (SSAM) tool. EVT models were developed to estimate the generalized Pareto (GP) distributions of both field-measured conflicts and simulated conflicts of different scenarios. The calibration results show considerable matching of the estimated GP distributions between simulated conflicts and field-measured conflicts. As such, the proposed calibration procedure for microsimulation model is recommended as a promising approach in simulation-based safety evaluation of signalized intersections.

Optimization-Based Calibration Process for Position-Sensitive Detector Systems

In this paper, a calibration process for position-sensitive detector (PSD) systems is proposed. In a PSD system using a quadrature detector (QD), various error sources including the QD, circuit components, and mechanical misalignment that appear in actual implementation introduce inaccuracies in the beam position estimation. The error pattern can be non-linear in the beam power, and non-uniform in the beam position. To calibrate the PSD and enhance the estimation accuracy, this work proposes an optimization-based calibration process. The proposed calibration process is comprehensive, correcting all errors at once in the final assembly state, which can reduce the calibration time and cost. Moreover, the result of the calibration is stable with respect to variations in the beam power, gain stage, and beam position. The impressive enhancement in accuracy and stability of beam position estimation is demonstrated experimentally.

A macroscopic approach for calibration and validation of a modified social force model for bidirectional pedestrian streams

The original social force model of pedestrians and its variants have been extensively studied in the past. However, little attention has been given to their parameter estimation and validation specifically for the environments with high density and complex phenomena such as self-organization and lane formation. This paper presents a macroscopic framework for calibration and validation of a modified social force model for bidirectional pedestrian streams based on the concept of pedestrian area-wide fundamental diagram, also known as pedestrian Macroscopic Fundamental Diagram (p-MFD). Results demonstrate that the proposed calibration process and the modified social force model can reproduce the empirically observed p-MFD with features such as hysteresis while consistently generating microscopic emergent self-organization and lane formation phenomena. Overall, validation and application results suggest that the calibrated model successfully replicates pedestrian traffic patterns and support the future applications of the model for various operations and planning purposes.

Integration of nighttime light remote sensing images and taxi GPS tracking data for population surface enhancement

ABSTRACTThe population distribution grid at fine scales better reflects the distribution of residents and plays an important role in investigating urban systems. The recent years have witnessed a growing trend of applying the nighttime light data to the estimation of population at micro levels. However, using the nighttime light data alone to estimate population may cause the overestimation problem due to excessively high light radiance in specific types of areas such as commercial zones and transportation hubs. In dealing with this issue, this study used taxi trajectory data that delineate people’s movements, and explored the utility of integrating the nighttime light and taxi trajectory data in the estimation of population in Shanghai at the spatial resolution of 500 m. First, the initial population distribution grid was generated based on the NPP-VIIRS nighttime light data. Then, a calibration grid was created with taxi trajectory data, whereby the initial population grid was optimized. The accuracy of the resultant population grid was assessed by comparing it with the refined survey data. The result indicates that the final population distribution grid performed better than the initial population grid, which reflects the effectiveness of the proposed calibration process.

Multiple location constraints based industrial robot kinematic parameter calibration and accuracy assessment

Kinematic calibration of industrial robots is an effective method of improving robot accuracy, and thus robot performance, especially when working with offline programming. The state-of-art industrial applications are lacking an easy-to-operate, reliable, and economic solution, hence forbidding frequent on-site calibration. This study presents a robot kinematic calibration method to improve the accuracy of six-axis industrial robots, using multiple location constraints. The robot parameters are calibrated by controlling a robot to reach the same location in different poses. Two standard devices and a non-contact equipment, non-bar device, are used for measurement. The proposed calibration process applies three identification methods and two compensation methods that can be mixed and matched, allowing flexible combinations of solutions to fit various industrial conditions. The proposed measurement/calibration system is economic, easy-to-operate, reliable, and suitable for express user-site industrial robot kinematic calibration, avoiding extensive production interruption. Actual experiments are carried out to verify the effects of joint zero calibration. These experiments demonstrate the proposed method’s ability to improve the accuracy of robots, and thus improve the robot work quality using offline programming.

A Cable-Drop Compensated LDO for Rechargeable Battery Powered Systems With Load Current Management in Two-Cable or Three-Cable Structures

This paper presents a low-dropout (LDO) regulator structure that is aimed at rechargeable battery powered systems where direct sensing of the load voltage is not available. The cable connecting the regulated output to the load may create a voltage drop and cause error to the load voltage. Conventional methods address this issue by increasing the LDO output voltage to compensate the cable voltage drop. The proposed architecture extends this idea by including a calibration block that updates the required compensation voltage to track the cable resistance shift due to cable length or temperature change. The measured cable-drop error was reduced from 2.4% to ∼0.1% by iterating the proposed calibration process three times. Under the condition of time-varying temperature, the measured calibration process effectively reduced the cable-drop error due to the temperature-coefficient of the cable resistance. The proposed system also includes a current management block, by which the priority is set between the load current and the battery charging current. This paper proposes two architectures, the two-cable and the three-cable structures, to implement both the cable-drop calibration and the current management functions. Other functions such as input under-voltage-lockout and output current-limiting are also included and have been verified by experiment.

Improvement of on‐wafer measurement accuracy with RF signal detection technique at millimetre‐wave frequencies

The study proposes an innovative method of improving calibration reproducibility in on-wafer measurements. First, an uncertainty analysis was conducted on a measurement system. Based on the analysis results, the probe positional error in the X, Y, and Z axes was considered the dominant error factor. In the proposed calibration process, the positions of the contact probes are adjusted in relation to defined origin coordinates that establish the electrical centre of the thru standard. Standard deviations of the measurements of short, load, and thru devices were significantly decreased using the proposed calibration system, indicating significant improvement in the stability of the calibration process. The proposed method also demonstrated the improvement of calibration reproducibility in a 75 Ω mismatched line device, compared to calibrations using conventional processes. The proposed calibration process is expected to contribute to eliminating operator dependence due to variation in the probe position in on-wafer measurements, and can potentially be applied to evaluations of a wide variety of planar circuits.

Calibration of digital optical phase conjugation setups based on orthonormal rectangular polynomials

Digital optical phase conjugation (DOPC) has proven to be a promising technique in deep tissue fluorescence imaging. Nonetheless, DOPC optical setups require precise alignment of all optical components to accurately read the wavefront of scattered light in a turbid medium and playback the conjugated beam toward the sample. Minor misalignments and possible imperfections in the arrangement or the structure of the optical components significantly reduce the performance of the method. In this paper, a calibration procedure based on orthogonal rectangular polynomials is introduced to compensate major imperfections including the optical aberration in the wavefront of the reference beam and the substrate curvature of the spatial light modulator without adding extra optical components to the original setup. The proposed algorithm also provides a systematic calibration procedure for mechanical fine tuning of DOPC systems. It is shown experimentally that the proposed calibration process improves the peak-to-background ratio when focusing light after passing through a highly scattering medium.

A Robust Design Optimization Framework for Systematic Model-Based Calibration of Engine Control Systems

In this paper, a systematic model-based calibration framework basing on robust design optimization technique is developed for engine control system. In this framework, the control system is calibrated in an optimization fashion where both performance and robustness of the closed-loop system to uncertainties are optimized. The proposed calibration process has three steps: in the first step, the optimal performance of the system at the nominal conditions, where the effects of uncertainties are ignored, is computed by formulation of the controller calibration as an optimization problem. The capabilities of the controller are fully explored at nominal conditions. In the second step, the robustness and sensitivity of a selected control design to the system uncertainties are analyzed using Monte Carlo simulation. In the third step, robust design optimization is applied to optimize both performance and robustness of the closed-loop system to the uncertainties. The robustness capabilities of the controller are fully explored and the one that satisfies both performance and robustness requirements is selected. This process is implemented for the calibration of an advanced diesel air path control system with a variable geometry turbocharger (VGT) and dual loop exhaust gas recirculation (EGR) architecture.

Development of State-Specific Load and Resistance Factor Rating Method

Recognizing the limitations of the generic truck weight data and conservative assumptions made during the calibration of live load factors for bridge rating, the AASHTO load and resistance factor rating (LRFR) manual for bridge evaluation provides sufficient flexibility and allows state agencies to adjust the live load factors based on their individual conditions and site-specific or state-specific information. This paper describes a reliability-based process that can be followed to perform such adjustments and illustrates its application using an example in which the procedure was followed during the calibration of a LRFR methodology for New York State bridges. This methodology is applied to the rating of existing bridges, posting of understrength bridges, and checking of permit trucks. The live load models used during the calibration are based on weigh-in-motion data collected from several representative sites. The LRFR live load factors developed using the proposed calibration process would provide uniform and consistent levels of bridge safety and reliability for the bridge classes and configurations targeted. The target reliability levels used during the calibration should reflect the experience gained by state bridge engineers from evaluation of existing bridges under current loading conditions.

A Calibration Method of Binocular Vision in Laser Remanufacturing Robot

As an advanced repair technology, the laser remanufacturing technology has been paid much more attentions recently. The authors previously studied the vision calibration by using the Matlab Calibration toolbox. Since the boundaries of a single image have to be specified manually, however, the Matlab toolbox based calibration method will be time consuming and low precision. This article continues the study of vision calibration for laser remanufacturing machine system and proposes a new binocular vision calibration method based on Halcon10.0 software. Experimental results show that the proposed calibration process consumes shorter time and is able to achieve higher precision.

Calibration of transient groundwater models using time series analysis and moment matching

A comprehensive and efficient approach is presented for the calibration of transient groundwater models. The approach starts with the time series analysis of the measured heads in observation wells using all active stresses as input series, which may include rainfall, evaporation, surface water levels, and pumping. The time series analysis results in the impulse response function of each stress at the observation well. For each impulse response function, the temporal moments M0 and M1 may be computed. Both moments fulfill differential equations that are equivalent to the differential equation for steady groundwater flow, with known values along physical boundaries. The model of M0 may be calibrated for the transmissivity, as it does not depend on the storage coefficient; the computed values of M0 at the observation wells are used for calibration. The model of M1 may be calibrated for the storage coefficient, once the transmissivity is known from the M0 model; the computed values of M1 at the observation wells are used for calibration. The approach is intended for systems that may be approximated as linear. In summary, our proposed calibration process for transient models reduces to the calibration of only two steady models. Several examples are given to demonstrate the accuracy and efficiency of the proposed approach.

G-EMME/2: Automatic Calibration Tool of the EMME/2 Transit Assignment Using Genetic Algorithms

This research presents an automatic procedure for calibrating transit-assignment model parameters. The calibration process targets the optimal set of parameter values by ensuring that the assignment output volumes match ridership volumes obtained from on-board surveys. Due to the combinatorial nature of the problem of interest, the proposed calibration process is automated using genetic algorithm techniques to find the best values for parameters through minimizing a “misfit” function. This study presents the new G-EMME/2 tool, which is an automatic calibration tool designed to find the optimal set of values for the transit-assignment model parameters implemented in the EMME/2 transportation planning software. The G-EMME/2 tool was applied to the Toronto transit network, and the five EMME/2 aggregate transit-assignment model parameters were estimated. The results are very encouraging. This research is an attempt to help automate the tedious process of calibrating transit assignment models.