Fast AHRS Filter for Accelerometer, Magnetometer, and Gyroscope Combination with Separated Sensor Corrections

A new predictor–corrector filter for attitude and heading reference systems (AHRS) using data from an orthogonal sensor combination of three accelerometers, three magnetometers and three gyroscopes is proposed. The filter uses the predictor—corrector structure, with prediction based on gyroscopes and independent correction steps for acceleration and magnetic field sensors. We propose two variants of the filter: (i) one using mathematical operations of special orthogonal group SO(3), that are accurate for nonlinear operations, for highest possible accuracy, and (ii) one using linearization of nonlinear operations for fast evaluation. Both approaches are quaternion-based filter realizations without redundant steps. The filters are compared to state of the art methods in this field on data recorded using low-cost microelectromechanical systems (MEMS) sensors with ground truth measured by the VICON optical system. Both filters achieved better accuracy than conventional methods at lower computational cost. The recorded data with ground truth reference and the source codes of both filters are publicly available.

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Evaluation of an Effective Engine Nozzle Map by Reduction of Data Acquired During Transient Operation

Volume 2: Turbo Expo 2004 ◽

10.1115/gt2004-53118 ◽

2004 ◽

Author(s):

M. Lichtsinder ◽

Y. Levy

Keyword(s):

Low Cost ◽

Engine Performance ◽

Fast Evaluation ◽

Engine Model ◽

Performance Predictions ◽

Effective Performance ◽

Using Data ◽

Engine Components ◽

Engine Map ◽

Transient Operations

This paper discusses low cost and fast evaluation of effective performance maps for engine components such as nozzles, turbines and compressors using data acquired during transient engine operations. The objective of the present study is to re-evaluate effective engine performance maps when not all the engine component maps are known. The work is equally relevant to account for manufacturing tolerances of different engines resulting in small differences in their performance. Disassembly and rebuilding of an engine as well as degradation in performance due to extensive usage can cause small variations in their performance. If the engine maps do not represent particular engine operations with precision, its performance predictions will differ from the actual characteristics. The engine map evaluation is carried out using data acquired during aircraft transient operations at different altitudes, Mach numbers, angles of attack, side slip angles and during post-stall. The method is based on a conventional dynamic engine model. The unknown engine map characteristics are excluded from the model while the corresponding numbers of some measured values are added to the model input. The evaluated map values are calculated using an inverse solution of the equations of the “shortened” mathematical model. Some jet engine maps may be evaluated simultaneously. Two examples for fragments of compressor and compressor/nozzle map evaluations are presented in this paper.

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Hybrid Magnetorheological Composites for Electric and Magnetic Field Sensors and Transducers

Nanomaterials ◽

10.3390/nano10102060 ◽

2020 ◽

Vol 10 (10) ◽

pp. 2060

Author(s):

Ioan Bica ◽

Eugen Mircea Anitas ◽

Liviu Chirigiu

Keyword(s):

Magnetic Field ◽

Silicone Oil ◽

Low Cost ◽

Relative Dielectric Constant ◽

Dielectric Materials ◽

Electrical Capacitance ◽

Magnetic Dipoles ◽

Magnetic Field Sensors ◽

Electrical Devices ◽

Recorded Data

We present a simple, low-cost, and environmental-friendly method for the fabrication of hybrid magnetorheological composites (hMCs) based on cotton fibers soaked with a mixture of silicone oil (SO), carbonyl iron (CI) microparticles, and iron oxide microfibers (μF). The obtained hMCs, with various ratios (Φ) of SO and μF, are used as dielectric materials for manufacturing electrical devices. The equivalent electrical capacitance and resistance are investigated in the presence of an external magnetic field, with flux density B. Based on the recorded data, we obtain the variation of the relative dielectric constant (ϵr′), and electrical conductivity (σ), with Φ, and B. We show that, by increasing Φ, the distance between CI magnetic dipoles increases, and this leads to significant changes in the behaviour of ϵr′ and σ in a magnetic field. The results are explained by developing a theoretical model that is based on the dipolar approximation. They indicate that the obtained hMCs can be used in the fabrication of magneto-active fibers for fabrication of electric/magnetic field sensors and transducers.

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THE INFLUENCE OF THE WIND SPEED PREDICTION ERROR ON THE SIZE OF THE STORAGE CONTROLLED OPERATION ZONE IN THE SYSTEM WITH THE WIND GENERATOR

Praci Institutu elektrodinamiki Nacionalanoi akademii nauk Ukraini ◽

10.15407/publishing2020.57.035 ◽

2020 ◽

Vol 2020 (57) ◽

pp. 35-41

Author(s):

K.S. Klen ◽

◽

M.K. Yaremenko ◽

V.Ya. Zhuykov ◽

◽

...

Keyword(s):

Wind Speed ◽

Prediction Error ◽

Average Energy ◽

Interpolation Formula ◽

Wind Speed Prediction ◽

Wind Generator ◽

Prediction Horizon ◽

Speed Prediction ◽

Using Data ◽

Predictor Corrector

The article analyzes the influence of wind speed prediction error on the size of the controlled operation zone of the storage. The equation for calculating the power at the output of the wind generator according to the known values of wind speed is given. It is shown that when the wind speed prediction error reaches a value of 20%, the controlled operation zone of the storage disappears. The necessity of comparing prediction methods with different data discreteness to ensure the minimum possible prediction error and determining the influence of data discreteness on the error is substantiated. The equations of the "predictor-corrector" scheme for the Adams, Heming, and Milne methods are given. Newton's second interpolation formula for interpolation/extrapolation is given at the end of the data table. The average relative error of MARE was used to assess the accuracy of the prediction. It is shown that the prediction error is smaller when using data with less discreteness. It is shown that when using the Adams method with a prediction horizon of up to 30 min, within ± 34% of the average energy value, the drive can be controlled or discharged in a controlled manner. References 13, figures 2, tables 3.

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Nanosecond Photodynamics Simulations of a Cis-Trans Isomerization Are Enabled by Machine Learning

10.26434/chemrxiv.13047863 ◽

2020 ◽

Author(s):

Jingbai Li ◽

Patrick Reiser ◽

André Eberhard ◽

Pascal Friederich ◽

Steven Lopez

Keyword(s):

Machine Learning ◽

Neural Networks ◽

Excited State ◽

Adaptive Sampling ◽

Computational Cost ◽

Ground Truth ◽

Absolute Error ◽

Photochemical Reactions ◽

Computational Techniques ◽

Full Potential

Photochemical reactions are being increasingly used to construct complex molecular architectures with mild and straightforward reaction conditions. Computational techniques are increasingly important to understand the reactivities and chemoselectivities of photochemical isomerization reactions because they offer molecular bonding information along the excited-state(s) of photodynamics. These photodynamics simulations are resource-intensive and are typically limited to 1–10 picoseconds and 1,000 trajectories due to high computational cost. Most organic photochemical reactions have excited-state lifetimes exceeding 1 picosecond, which places them outside possible computational studies. Westermeyr et al. demonstrated that a machine learning approach could significantly lengthen photodynamics simulation times for a model system, methylenimmonium cation (CH2NH2+).We have developed a Python-based code, Python Rapid Artificial Intelligence Ab Initio Molecular Dynamics (PyRAI2MD), to accomplish the unprecedented 10 ns cis-trans photodynamics of trans-hexafluoro-2-butene (CF3–CH=CH–CF3) in 3.5 days. The same simulation would take approximately 58 years with ground-truth multiconfigurational dynamics. We proposed an innovative scheme combining Wigner sampling, geometrical interpolations, and short-time quantum chemical trajectories to effectively sample the initial data, facilitating the adaptive sampling to generate an informative and data-efficient training set with 6,232 data points. Our neural networks achieved chemical accuracy (mean absolute error of 0.032 eV). Our 4,814 trajectories reproduced the S1 half-life (60.5 fs), the photochemical product ratio (trans: cis = 2.3: 1), and autonomously discovered a pathway towards a carbene. The neural networks have also shown the capability of generalizing the full potential energy surface with chemically incomplete data (trans → cis but not cis → trans pathways) that may offer future automated photochemical reaction discoveries.

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Reduced basis approximations of the solutions to spectral fractional diffusion problems

Journal of Numerical Mathematics ◽

10.1515/jnma-2019-0053 ◽

2020 ◽

Vol 28 (3) ◽

pp. 147-160

Author(s):

Andrea Bonito ◽

Diane Guignard ◽

Ashley R. Zhang

Keyword(s):

Computational Cost ◽

Fractional Power ◽

Reaction Diffusion ◽

Fractional Diffusion ◽

Diffusion Problem ◽

Quadrature Point ◽

Reduced Basis ◽

Fast Evaluation ◽

Bottle Neck ◽

Diffusion Problems

AbstractWe consider the numerical approximation of the spectral fractional diffusion problem based on the so called Balakrishnan representation. The latter consists of an improper integral approximated via quadratures. At each quadrature point, a reaction–diffusion problem must be approximated and is the method bottle neck. In this work, we propose to reduce the computational cost using a reduced basis strategy allowing for a fast evaluation of the reaction–diffusion problems. The reduced basis does not depend on the fractional power s for 0 < smin ⩽ s ⩽ smax < 1. It is built offline once for all and used online irrespectively of the fractional power. We analyze the reduced basis strategy and show its exponential convergence. The analytical results are illustrated with insightful numerical experiments.

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Classification of Cattle Behaviours Using Neck-Mounted Accelerometer-Equipped Collars and Convolutional Neural Networks

Sensors ◽

10.3390/s21124050 ◽

2021 ◽

Vol 21 (12) ◽

pp. 4050

Author(s):

Dejan Pavlovic ◽

Christopher Davison ◽

Andrew Hamilton ◽

Oskar Marko ◽

Robert Atkinson ◽

...

Keyword(s):

Neural Network ◽

Model Performance ◽

Ground Truth ◽

Practical Implementation ◽

Ground Truth Data ◽

Battery Lifetime ◽

Implementation Challenges ◽

Memory Footprint ◽

Commercial Farms ◽

Using Data

Monitoring cattle behaviour is core to the early detection of health and welfare issues and to optimise the fertility of large herds. Accelerometer-based sensor systems that provide activity profiles are now used extensively on commercial farms and have evolved to identify behaviours such as the time spent ruminating and eating at an individual animal level. Acquiring this information at scale is central to informing on-farm management decisions. The paper presents the development of a Convolutional Neural Network (CNN) that classifies cattle behavioural states (`rumination’, `eating’ and `other’) using data generated from neck-mounted accelerometer collars. During three farm trials in the United Kingdom (Easter Howgate Farm, Edinburgh, UK), 18 steers were monitored to provide raw acceleration measurements, with ground truth data provided by muzzle-mounted pressure sensor halters. A range of neural network architectures are explored and rigorous hyper-parameter searches are performed to optimise the network. The computational complexity and memory footprint of CNN models are not readily compatible with deployment on low-power processors which are both memory and energy constrained. Thus, progressive reductions of the CNN were executed with minimal loss of performance in order to address the practical implementation challenges, defining the trade-off between model performance versus computation complexity and memory footprint to permit deployment on micro-controller architectures. The proposed methodology achieves a compression of 14.30 compared to the unpruned architecture but is nevertheless able to accurately classify cattle behaviours with an overall F1 score of 0.82 for both FP32 and FP16 precision while achieving a reasonable battery lifetime in excess of 5.7 years.

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MEMS Based SINS/OD Filter for Land Vehicles’ Applications

Mathematical Problems in Engineering ◽

10.1155/2017/1691320 ◽

2017 ◽

Vol 2017 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Huisheng Liu ◽

Zengcai Wang ◽

Susu Fang ◽

Chao Li

Keyword(s):

Navigation System ◽

Velocity Measurement ◽

Microelectromechanical Systems ◽

Low Cost ◽

Detection Algorithm ◽

Measurement Unit ◽

Integrated Navigation ◽

Integrated Navigation System ◽

Land Vehicles ◽

Mems Imu

A constrained low-cost SINS/OD filter aided with magnetometer is proposed in this paper. The filter is designed to provide a land vehicle navigation solution by fusing the measurements of the microelectromechanical systems based inertial measurement unit (MEMS IMU), the magnetometer (MAG), and the velocity measurement from odometer (OD). First, accelerometer and magnetometer integrated algorithm is studied to stabilize the attitude angle. Next, a SINS/OD/MAG integrated navigation system is designed and simulated, using an adaptive Kalman filter (AKF). It is shown that the accuracy of the integrated navigation system will be implemented to some extent. The field-test shows that the azimuth misalignment angle will diminish to less than 1°. Finally, an outliers detection algorithm is studied to estimate the velocity measurement bias of the odometer. The experimental results show the enhancement in restraining observation outliers that improves the precision of the integrated navigation system.

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Event-Locked Time-Resolved Fourier Spectroscopy

Applied Spectroscopy ◽

10.1366/0003702971941917 ◽

1997 ◽

Vol 51 (8) ◽

pp. 1106-1112 ◽

Cited By ~ 20

Author(s):

H. Weidner ◽

R. E. Peale

Keyword(s):

Signal To Noise Ratio ◽

Low Cost ◽

Michelson Interferometer ◽

Far Infrared ◽

Time Base ◽

The Novel ◽

Time Resolved ◽

Mathematical Algorithm ◽

Scan Time ◽

Recorded Data

A low-cost method of adding time-resolving capability to commercial Fourier transform spectrometers with a continuously scanning Michelson interferometer has been developed. This method is specifically designed to eliminate noise and artifacts caused by mirror-speed variations in the interferometer. The method exists of two parts: (1) a novel timing scheme for synchronizing the transient events under study and the digitizing of the interferogram and (2) a mathematical algorithm for extracting the spectral information from the recorded data. The novel timing scheme is a modification of the well-known interleaved, or stroboscopic, method. It achieves the same timing accuracy, signal-to-noise ratio, and freedom from artifacts as step-scan time-resolving Fourier spectrometers by locking the sampling of the interferogram to a stable time base rather than to the occurrences of the HeNe fringes. The necessary pathlength-difference information at which samples are taken is obtained from a record of the mirror speed. The resulting interferograms with uneven pathlength-difference spacings are transformed into wavenumber space by least-squares fits of periodic functions. Spectra from the far-infrared to the upper visible at resolutions up to 0.2 cm−1 are used to demonstrate the utility of this method.

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Status Estimation and In-Process Connection of Kanbans Using BLE Beacons and LPWA Network to Implement Intra-Traceability for the Kanban System

Sensors ◽

10.3390/s21155038 ◽

2021 ◽

Vol 21 (15) ◽

pp. 5038

Author(s):

Kosuke Shima ◽

Masahiro Yamaguchi ◽

Takumi Yoshida ◽

Takanobu Otsuka

Keyword(s):

Inventory Management ◽

Low Cost ◽

Computational Cost ◽

Low Energy ◽

Manufacturing Strategy ◽

Implementation Cost ◽

Measurement Systems ◽

Process Route ◽

Kanban System ◽

Low Computational Cost

IoT-based measurement systems for manufacturing have been widely implemented. As components that can be implemented at low cost, BLE beacons have been used in several systems developed in previous research. In this work, we focus on the Kanban system, which is a measure used in manufacturing strategy. The Kanban system emphasizes inventory management and is used to produce only required amounts. In the Kanban system, the Kanban cards are rotated through the factory along with the products, and when the products change to a different process route, the Kanban card is removed from the products and the products are assigned to another Kanban. For this reason, a single Kanban cannot trace products from plan to completion. In this work, we propose a system that uses a Bluetooth low energy (BLE) beacon to connect Kanbans in different routes but assigned to the same products. The proposed method estimates the beacon status of whether the Kanban is inside or outside a postbox, which can then be computed by a micro controller at low computational cost. In addition, the system connects the Kanbans using the beacons as paired connection targets. In an experiment, we confirmed that the system connected 70% of the beacons accurately. We also confirmed that the system could connect the Kanbans at a small implementation cost.

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RF-MEMS Components and Networks for High-Performance Reconfigurable Telecommunication and Wireless Systems

Advances in Science and Technology ◽

10.4028/www.scientific.net/ast.81.65 ◽

2012 ◽

Vol 81 ◽

pp. 65-74 ◽

Cited By ~ 4

Author(s):

Jacopo Iannacci ◽

Giuseppe Resta ◽

Paola Farinelli ◽

Roberto Sorrentino

Keyword(s):

High Performance ◽

Microelectromechanical Systems ◽

Rf Mems ◽

Low Cost ◽

Impedance Matching ◽

Phase Shifters ◽

Rf Systems ◽

Mems Technology ◽

And Performance ◽

Rf Performance

MEMS (MicroElectroMechanical-Systems) technology applied to the field of Radio Frequency systems (i.e. RF-MEMS) has emerged in the last 10-15 years as a valuable and viable solution to manufacture low-cost and very high-performance passive components, like variable capacitors, inductors and micro-relays, as well as complex networks, like tunable filters, reconfigurable impedance matching networks and phase shifters, and so on. The availability of such components and their integration within RF systems (e.g. radio transceivers, radars, satellites, etc.) enables boosting the characteristics and performance of telecommunication systems, addressing for instance a significant increase of their reconfigurability. The benefits resulting from the employment of RF-MEMS technology are paramount, being some of them the reduction of hardware redundancy and power consumption, along with the operability of the same RF system according to multiple standards. After framing more in detail the whole context of RF MEMS technology, this paper will provide a brief introduction on a typical RF-MEMS technology platform. Subsequently, some relevant examples of lumped RF MEMS passive elements and complex reconfigurable networks will be reported along with their measured RF performance and characteristics.

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