Average Transfer Function Research Articles

Impact of pupil size and corneal spherical aberrations on the performance of monofocal intraocular lenses: an experimental model

In this study, an in vitro comparison of the optical performances of three models (spherical, aberration-neutral, and aberration-correcting) of monofocal intraocular lenses (IOLs) is proposed. A comprehensive model is employed, encompassing a wide range of corneal models and aperture sizes, reflecting the high variability of corneal spherical aberrations (SA) and pupil sizes in both normal and postoperative refractive corneal surgery populations. Analysis of average through-focus modulation transfer function (MTF) curves reveals significant differences in optical performance attributable to pupil size and corneal SA. These differences depend on the IOL model and affects MTFmax (representing contrast at best focus), depth of focus, refractive error tolerance, and the effective power of the lens.

Improved performance of three mirror anastigmat telescope with freeform surface: Optical design, testing and validation aspects

"In this paper, the optical design of a Three Mirror Anastigmat (TMA) Telescope is modified by substitution of a convex freeform secondary and optimization carried out to obtain improved performance. The proposed convex freeform surface is precisely manufactured using the bonnet polishing technique and tested with a sub-aperture stitched algorithm, meeting the specified surface accuracy requirements. Further, to validate the design, the realized secondary freeform optic is tested in conjunction with primary and tertiary optics in the conceived TMA configuration. The telescope system performance is established using a double-pass interferometric test setup. The modified design enhances the telescope system's performance in the extended field of view (FoV) from ±2.5° to ±3.5° across the track and from ±0.4° to ±0.6° along the track. Measured performance results demonstrate an average modulation transfer function (MTF) of 0.56 and an average Strehl ratio of 0.64 at all field points. The effective focal length of the system is computed to be 975 mm. In summary, the proposed freeform surface significantly improves the optical system performance within the available real estate of the envisaged space telescope system."

Investigation on the role of the finger Transfer Function in tactile rendering by Friction-Induced-Vibrations

The world of haptics, tactile rendering of textures and tactile interfaces has witnessed significant expansion in the last years. When dealing with the design of tactile devices, the interaction between the device and the user's finger becomes crucial. With a focus on optimizing vibrotactile devices for texture rendering, a parametric analysis of the dynamic transfer function of the human finger was conducted under different test conditions. Discrimination campaigns have been conducted, exploiting an average transfer function among participants, to simulate surface textures by Friction-Induced Vibrations. The excellent results of the discrimination campaigns evidenced the effectiveness of the approach, allowing to get rid of the need to characterize the specific finger Transfer Function for each user of the vibrotactile device.

Analysis of data from the full-scale prototype testing of the WASP – A novel wave measuring buoy.

To assess the viability of locations for wave energy farms, and design effective coastal protection measures, knowledge of local wave regimes is required. Current regime-measuring devices are expensive, and the aim of the WASP Project is to develop a low-cost, self-powering wave-measuring device. The Wave-Activated Sensor Power Buoy (WASP) comprises a floating body with a moonpool. The relative motion of the water level in the moonpool to the buoy will pressurise and depressurise the air above the water column, which will be used to drive a bidirectional turbine in the manner of an oscillating water column, which will operate in conjunction with a generator to recharge an on-board battery pack. It has previously been demonstrated through tank testing of scale-models that a sea-state may be estimated from measurements of the pressure within the air above the water column under controlled conditions [1]. Important statistical parameters relating to the sea state, such as the significant wave height, zero-cross period et cetera. may then be estimated from the spectral moments of the wave spectrum [2].
 This paper seeks to validate the use of measurements taken of the pressure in a volume of air contained in a chamber above an oscillating water column (OWC) (which is in communication with the ocean) to estimate the sea state which induces motion of the water column.
 The WASP was deployed from March to July 2019 at the Smart Bay test facility in Galway Bay, Ireland. The ¼ Scale test site was previously characterised by B Cahill UCC 2011 [3] using data captured by the Marine Institute Datawell WaveRider buoy from 2006 to 2011. Pressure signal data recorded by the WASP at a frequency of 8Hz was processed in to 30-minutes blocks to reflect the presented data from the WaveRider buoy, from which the WASP was moored a distance of 400m from during deployment. Power Density Spectra for 6,500 thirty-minute sea states were generated and an inverse transfer function between the WASP and the WaveRider produced. This allowed for the calculation of the associated significant wave height, Hs, and zero-crossing period, Tz, from the WASP pressure data for each thirty-minute block of data. At this time, outliers and bimodal spectra were removed to simplify the analysis, and the data was binned based on Hs and Tz ranges. For each bin, average inverse transfer functions were generated. A Bretschneider Spectrum [4] was produced using the Hs and Tz values from the WaveRider data for the respective binned WASP data. An average transfer function was then generated between the Bretschneider models and the corresponding sea states for the WASP. Using this final transfer function, a scatter plot of Hs and Tz for the test site was generated and compared against the previously produced scatter plot from the initial resource characterisation of the Galway Bay Test Site in 2011 in order to determine if the WASP is capable of measuring sea-states through measurement of time series pressure signals in the volume of air above the water column in the OWC.

Water Flow Modeling and Forecast in a Water Branch of Mexico City through ARIMA and Transfer Function Models for Anomaly Detection

Early identification of anomalies (such as leakages or sensor failures) in urban water distribution systems is critical to mitigating water scarcity in cities and is a challenge in water resource management. Several data-driven methods based on machine learning algorithms have been proposed in the literature for leakage detection in urban water distribution systems. Still, most of them are challenging to implement due to their complexity and requirements of vast amounts of reliable data for proper model generation. In addition, the required infrastructure and instrumentation to collect the data needed to train the models could be unaffordable. This paper presents the use and comparison of Autoregressive Integrated Moving Average models and Transfer Function models generated via the Box–Jenkins approach to modeling the water flow in water distribution systems for anomaly detection. The models were fit using water flow data from tanks operating in a branch of the water distribution system of Mexico City. The results showed that both methods helped select the best model type for each variable in the analyzed water branch, with Seasonal ARIMA models achieving a lower mean absolute percentage error than the fitted Transfer Function models. Furthermore, this methodology can be adjusted to different time windows to generate alerts at different rates and does not require a large sample size. The generated anomaly detection models could improve the efficiency of the water distribution system by detecting anomalies such as wrong measurements and water leakages.

A Unified Switched Nonlinear Dynamic Model of an Electric Vehicle for Performance Evaluation

The advanced modeling and estimation of overall system dynamics play a vital role in electric vehicles (EVs), as the selection of components in the powertrain and prediction of performance are the key market qualifiers. The state-space averaged model and small-signal transfer function model are useful for assessing long-term behavior in system-level analysis and for designing the controller parameters, respectively. Both models take less computation time but ignore the high-frequency switching dynamics. Therefore, these two models could be impractical for the development and testing of EV prototypes. On the other hand, the multi-domain model in available simulation tools gives in-depth information about the short-term behavior and loss analysis of power electronic devices in each subsystem, considering the switching dynamics in a long computation time. In this paper, a general mathematical framework for the dynamical analysis of complete EVs is presented using a unified, switched nonlinear model. This equation-based model runs faster than the available module-based simulation tools. Two other models, namely the time domain state-space averaged model and frequency domain small-signal transfer function model, are also developed from the switched nonlinear model for the analysis with less computation time. The design and performance of an EV with two different motors and its controllers are evaluated using the general mathematical framework.

A study on transfer function to estimate the central aortic blood pressure waveform

Noninvasive measurement of the central aortic blood pressure has become an important technique that has generated a lot of interest around the medicine industry because it can estimate the central aortic blood pressure waveform without inserting a pressure-sensing catheter into the ascending aorta. The accuracy of noninvasive estimation of aortic hemodynamics and cardiac contractility is still debatable in noninvasive measurement of the central aortic blood methods. The objective of this project is to investigate the transfer functions available for converting radial blood pressure waveforms to central aortic blood pressure waveforms. In this project, three different transfer functions will be investigated which are The Generalized Transfer Function, N-Point Moving Average and Adaptive Transfer Function in order to recommend the effective method in terms of accuracy. The study methodology will be conducted through the software MATLAB R2021b. The investigation of these three methods will be conducted with data collected from virtual subjects from the HaeMod database. The Generalized transfer function, N-Point Moving Average and Adaptive Transfer Function will be coded, evaluated, and analyzed as part of the methodology. The determination of the most effective method among the three transfer functions will be attributed according to output comparison of Systolic peak differences, the RMSE and the MAPE between the estimated central aortic blood pressure and the measured central aortic blood pressure.

Dynamic force identification in milling based on IRLS using acceleration signals

Measurement of cutting force is important for in-process monitoring, control and optimization. However, it is very difficult to measure the cutting force directly using invasive sensor in industrial scene. This paper develops an infinite-time recursive identification method of cutting force under finite buffer length condition, called the improved recursive least squares (IRLS) method. A cutting force identification framework based on time-domain convolutional theory is introduced, where the cutting force is identified using the acceleration signal easily obtained from industrial scene. Then, the decay characteristic of the impulse response function and the recursive characteristic of the transfer matrix are used to improve the recursive least squares method. The IRLS method overcomes the data saturation problem of the recursive least squares method and can identify the cutting force in infinite time. To reduce the error amplification of the proposed cutting force identification method, the averaged transfer function is used to determine the length of the buffer. In addition, the compensated values of the Kistler 9129AA dynamometer measurement results are used as a reference. Finally, several sets of milling experiments are performed to verify the effectiveness and rationality of the IRLS method.

Reduction and reconstruction strategy of active thermal control system based on unsupervised learning and thermo-optics for spaceborne high-resolution remote sensor

The development of small Earth observation satellites with high performance optical remote sensors has received much attention in recent years due to its responsiveness and immediacy. As one of the most resource-intensive subsystems of spacecrafts, the active thermal control system (ATCS) should be optimized; however, manual thermal design does not guarantee an optimal solution and requires months. For this purpose, we presented a ATCS’s reduction and reconstruction strategy based on an unsupervised learning framework, in which factor loadings are applied to combine kernel-based principal component analysis and Gaussian mixture model clustering. This strategy was implemented on a spaceborne high-resolution remote sensor (HRS) with 0.5 m ground sample distance. As a result, with the cumulative variance contribution rate > 90 % and 10 Gaussian distributions, the reconstructed ATCS of HRS had a 78.6 % reduction rate and took only 3 h, which suggests the high efficiency and low computational cost of the proposed strategy. Finally, the performed orbital thermal and thermo-optical integrated analyses indicated that temperature fluctuations were within ± 0.02–0.6 °C and optical surface errors were within the tolerance. The average modulation transfer function in the tangential and sagittal directions decreased by only 2 % and 2.5 %, respectively, and the radius of the spot root mean square was considerably smaller than the size of one pixel (8.75 μm). These results prove the feasibility and validity of the proposed strategy. This study solved the problem of identifying the optimal ATCS for optical remote sensors and significantly reducing the ATCS’s resource occupancy, which provided a reliable research basis for the development of high-performance small Earth observation satellites. Additionally, the proposed strategy is versatile and can be used in thermal engineering applications of various complex spacecrafts and payloads.

Predicting Geostationary 40–150 keV Electron Flux Using ARMAX (an Autoregressive Moving Average Transfer Function), RNN (a Recurrent Neural Network), and Logistic Regression: A Comparison of Models

AbstractWe screen several algorithms for their ability to produce good predictive models of hourly 40–150 keV electron flux at geostationary orbit (data from GOES‐13) using solar wind, Interplanetary Magnetic Field, and geomagnetic index parameters that would be available for real time forecasting. Value‐predicting models developed using ARMAX (autoregressive moving average transfer function), RNN (recurrent neural network), or stepwise‐reduced regression produced roughly similar results. Including magnetic local time as a categorical variable to describe both the differing levels of flux and the differing influence of parameters improved the models (r as high as 0.814; Heidke Skill Score (HSS) as high as 0.663), however value‐predicting models did a poor job at predicting highs and lows. Diagnostic tests are introduced (cubic fit to observation‐prediction relationship and Lag1 correlation) that better assess predictions of extremes than single metrics such as root mean square error, mean absolute error, or median symmetric accuracy. Classifier models (RNN and logistic regression) were equally able to predict flux rise above the 75th percentile (HSS as high as 0.667). Logistic regression models were improved by the addition of multiplicative interaction and quadratic terms. Only predictors from 1 or 3 hr before were necessary and a detailed description of flux time series behavior was not needed. Stepwise selection of these variables trimmed non‐contributing parameters for a more parsimonious and portable logistic regression model that predicted as well as neural network‐derived models. We provide a logistic regression model (LL3: LogisticLag3) based on inputs measured 3 hr previous, along with optimal probability thresholds, for future predictions.

Models for "Predicting geostationary 40-150 keV electron flux using ARMAX (an autoregressive moving average transfer function), RNN (a recurrent neural network), and logistic regression: a comparison of models"

Models for "Predicting geostationary 40-150 keV electron flux using ARMAX (an autoregressive moving average transfer function), RNN (a recurrent neural network), and logistic regression: a comparison of models"

Determining the Timing of Driver Influences on 1.8–3.5 MeV Electron Flux at Geosynchronous Orbit Using ARMAX Methodology and Stepwise Regression

AbstractAlthough lagged correlations have suggested influences of solar wind velocity (V) and number density (N), Bz, ultralow frequency (ULF) wave power, and substorms (as measured by the auroral electrojet (AE) index) on MeV electron flux at geosynchronous orbit over an impressive number of hours and days, a satellite's diurnal cycle can inflate correlations, associations between drivers may produce spurious effects, and correlations between all previous time steps may create an appearance of additive influence over many hours. Autoregressive‐moving average transfer function (ARMAX) multiple regressions incorporating previous hours simultaneously can eliminate cycles and assess the impact of parameters, at each hour, while others are controlled. ARMAX influences are an order of magnitude lower than correlations uncorrected for time behavior. Most influence occurs within a few hours, not the many hours suggested by correlation. A log transformation accounts for nonlinearities. Over all hours, solar wind velocity (V) and number density (N) show an initial negative impact, with longer term positive influences over the 9 (V) or 27 (N) hr. Bz is initially a positive influence, with a longer term (6 hr) negative effect. ULF waves impact flux in the first (positive) and second (negative) hour before the flux measurement, with further negative influences in the 12–24 hr before. AE (representing electron injection by substorms) shows only a short term (1 hr) positive influence. However, when only recovery and after‐recovery storm periods are considered (using stepwise regression), there are positive influences of ULF waves, AE, and V, with negative influences of N and Bz.

Data-driven local average room transfer function estimation for multi-point equalization.

Multi-point room equalization (EQ) aims to achieve a desired sound quality within a wider listening area than single-point EQ. However, multi-point EQ necessitates the measurement of multiple room impulse responses at a listener position, which may be a laborious task for an end-user. This article presents a data-driven method that estimates a spatially averaged room transfer function (RTF) from a single-point RTF in the low-frequency region. A deep neural network (DNN) is trained using only simulated RTFs and tested with both simulated and measured RTFs. It is demonstrated that the DNN learns a spatial smoothing operation: notches across the spectrum are smoothed out while the peaks of the single-point RTF are preserved. An EQ framework based on a finite impulse response filter is used to evaluate the room EQ performance. The results show that while not fully reaching the level of multi-point EQ performance, the proposed data-driven local average RTF estimation method generally brings improvement over single-point EQ.

Using ARMAX Models to Determine the Drivers of 40-150keV GOES Electron Fluxes.

We investigate the drivers of 40–150 keV hourly electron flux at geostationary orbit (GOES 13) using autoregressive moving average transfer functions (ARMAX) multiple regression models which remove the confounding effect of diurnal cyclicity and allow assessment of each parameter independently. By taking logs of the variables, we create nonlinear models. While many factors show high correlation with flux in single variable analysis (substorms, ULF waves, solar wind velocity (V), pressure (P), number density (N) and electric field (E y ), IMF Bz, Kp, and SymH), ARMAX models show substorms are the dominant influence at 40–75 keV and over 20–12 MLT, with little difference seen between disturbed and quiet periods. The Ey influence is positive post‐midnight, negative post‐noon. Pressure shows a negative influence, strongest at 150 keV. ULF waves are a more modest influence than suggested by single variable correlation. Kp and SymH show little effect when other variables are included. Using path analysis, we calculate the summed direct and indirect influences through the driving of intermediate parameters. Pressure shows a summed direct and indirect influence nearly half that of the direct substorm effect. N, V, and B z , as indirect drivers, are equally influential. While simple correlation or neural networks can be used for flux prediction, neither can effectively identify drivers. Instead, consideration of physical influences, removing cycles that artificially inflate correlations, and controlling the effects of other parameters gives a clearer picture of which are most influential in this system.

Freeform wide-angle camera lens enabling mitigable distortion.

Allowing natural scenes as well as maximizing field of view (FoV) can benefit from the minimization of distortion for the wide-angle camera. The wide-angle camera utilizing freeform surfaces for mitigating distortions, either barrel distortion or pincushion distortion, is therefore of interest. In this paper, the designs of using all-aspherical surfaces and aspherical surfaces combined with freeform surfaces are investigated. To minimize the deviation before and after converting from aspherical surfaces to freeform surfaces, a mathematical conversion scheme is derived. By applying it to the design example, the methodology is shown to be effective in the case of an optical system with a large number of aspherical/freeform surfaces. Additionally, custom freeform analysis tools are developed for quantitative analysis and visualization of the critical characteristics of optical performance, namely, a 2D lateral color field map, 2D relative illumination field map, 2D spot radius field map, and 2D average modulation transfer function (MTF) field map. Compared to classical all-aspherical design, simulation results show that freeform design has the capability to reduce distortion, and other performances such as relative illumination, spot size, and MTF can also be improved, even though there are some compromises on the peripheral FoV. The design approach will have potential important research and application values for lens systems utilized in miniature camera lenses, especially the wide FoV capability.

Comprehensive design analysis and verification of space-based short-wave infrared coded spectrometer via curved prism dispersion.

The spaceborne dispersive spectrometer is widely used in environmental, resource, and ocean observations. The coded spectrometer has higher energy advantages than the dispersion spectrometer, so it has great application prospects. In the current study, we developed an off-axis short-wave infrared coded optical system (SICOS) based on curved prism dispersion, and we further explored the design and optimization of the SICOS structure. Finite element analyses of a space-based short-wave infrared coded spectrometer based on curved prism dispersion (SSICS-CPD), including static simulation, modal analysis, sinusoidal vibration mechanical analysis, and random vibration mechanical analysis, were carried out. Simulation results showed that the SICOS support structure had excellent mechanical and thermal stability. As off-axis optical systems cannot meet the requirements of optical position accuracy through centering processing, a point source microscope and three-coordinate measuring machines were employed to complete the high-precision and rapid assembly of the SSICS-CPD. In addition, verification tests of surface shape error, stress relief, random vibration, and optical design parameters were carried out to validate the high stability and imaging performance of the SSICS-CPD. Results showed that the average modulation transfer function in the full field was 0.43 at 16.67 lp/mm, the spectral smile was <0.2 pixels, and the spectral keystone was <0.1 pixels. The design, analysis, assembly, and verification of the SSICS-CPD provide a useful reference for the development of other spaceborne prism dispersion spectrometers.

Research on thermal design and thermal optical performance of space telescope based on multidisciplinary integration

This paper first analyzes the external heat flow of a low-orbit space telescope in different flight attitudes, and determines the position of the heat dissipation surface and the thermal analysis cases. Then, the detailed thermal design of each component of the telescope is completed to reduce the influence of thermal deformation of optical elements and supporting structures caused by temperature changes on the imaging quality of telescope. Especially for the thermal control difficulties of CCD detectors such as large heat generation in a short time and one-dimensional movement in a narrow space, a segmented proprietary cold chain with flexible section is designed to transfer the heat to the radiant cold plate. Finally, the thermal/structure/optical integrated simulation analysis under extreme cases is carried out. It is concluded that the average modulation transfer function (MTF) of the optical system at the cutoff frequency satisfies the design requirement greater than 0.3. The analysis results show that the thermal control system designed in this paper can ensure the optical performance of the telescope, which has important reference significance for the thermal design of other space telescopes.

Optical design of an integrated imaging system of optical camera and synthetic aperture radar.

This paper presents an integrated imaging system of optical camera and synthetic aperture radar (SAR). The system can realize 400 nm-900 nm visible and near infrared band and 35 GHz microwave Ka band dual-band imaging. Compared with the single band imaging system, the observation ability and environmental adaptability of the integrated imaging system have been significantly improved. The optical camera shares a common front system with the synthetic aperture radar. After simulation, the average modulation transfer function (MTF) of 50 line pairs per millimeter (lp/mm) of the optical subsystem is 0.47. In addition, a principle prototype with a pupil diameter of 210 mm was developed to verify the performance of synthetic aperture radar antennas. After the experimental test, the SAR radiation pattern simulation results are in good conformity with the measured results, which are in line with the expected results.

Design of a Dual-Band Compact Integrated Remote Sensing System for Visible Light and Long-Wave Infrared

This paper presents a design of a dual-band integrated space telescope system for visible light and long-wave infrared. The system can simultaneously image the visible light band of 450–900 nm and the long-wave infrared band of 7700–10,500 nm. The dual-band integrated imaging system can freely switch the observation band to adapt to different scenes and environmental changes. The camera can also further expand its capabilities in the fields of multi-spectral observation and low-light observation by collocation with different detectors. This design is based on a coaxial reflection system, the two bands share the camera’s primary and secondary mirrors, and the separation of the two bands is achieved through a separate field of view design. After simulation, the average Modulation Transfer Function (MTF) value of the visible light band of the system at 50 lp/mm (line pairs per millimeter) reaches 0.45, and the average MTF value of the long-wave infrared band at 50 lp/mm reaches 0.36. In addition, tolerance analysis, ambient temperature analysis and transmittance analysis of the integrated system are carried out in this paper to further improve the integrated system scheme, and the feasibility of the system is further verified.

Small-signal model and control approach for a dual input boost converter with VMC

ABSTRACT The dual-input boost converter (DIBC) with voltage multiplier cell (VMC) and operating in continuous conduction mode (CCM) is feasible for applications with high voltage from low voltage renewable energy sources (RES). To achieve a high voltage gain, DIBC is operated with two VMC, and overlapping switch signals, i.e. at duty ratio higher than 0.5; these complicate the modelling and control design. The objective here is to achieve output voltage regulation under load and input voltage disturbances with the proposed feed-forward plus feedback (FFFB) control strategy for DIBC with two VMC. Nevanlinna–Pick interpolation method and MATLAB SISOtool are used to design the optimally stable feed-forward controller and feedback controller, respectively. The study of the non-minimum phase behaviour of the converter, followed by the control design, is done based on the derived averaged state-space small-signal transfer function models. The analytical model is validated using MATLAB and PSIM software and experimentally. A converter prototype of 250 W is built and experimentally tested; the control is realised using FPGA. The simulation and experimental results ensure that the converter with this proposed control design provides satisfactory voltage regulation.