A Study on DTW-based RUL Estimation Algorithm of Propulsion Motor: Case Study

AbstractWhile performing statistical–dynamical simulations for avalanche predetermination, a propagation model must reach a compromise between precise description of the avalanche flow and computation times. Crucial problems are the choice of appropriate distributions describing the variability of the different inputs/outputs and model identifiability. In this study, a depth-averaged propagation model is used within a hierarchical Bayesian framework. First, the joint posterior distribution is estimated using a sequential Metropolis–Hastings algorithm. Details for tuning the estimation algorithm are provided, as well as tests to check convergence. Of particular interest is the calibration of the two coefficients of a Voellmy friction law, with model identifiability ensured by prior information. Second, the point estimates are used to predict the joint distribution of different variables of interest for hazard mapping. Recent developments are employed to compute pressure distributions taking into account the rheology of snow. The different steps of the method are illustrated with a real case study, for which all possible decennial scenarios are simulated. It appears that the marginal distribution of impact pressures is strongly skewed, with possible high values for avalanches characterized by low Froude numbers. Model assumptions and results are discussed.

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Optimal Placement of Actuators Via Sparse Learning for Composite Fuselage Shape Control

Journal of Manufacturing Science and Engineering ◽

10.1115/1.4044249 ◽

2019 ◽

Vol 141 (10) ◽

Cited By ~ 2

Author(s):

Juan Du ◽

Xiaowei Yue ◽

Jeffrey H. Hunt ◽

Jianjun Shi

Keyword(s):

Shape Control ◽

Estimation Algorithm ◽

Fixed Number ◽

Optimal Placement ◽

Sparse Learning ◽

Parameter Estimation Algorithm ◽

Dimensional Shape ◽

Shape Adjustment ◽

Actuator Placement

Shape control is a critical task in the composite fuselage assembly process due to the dimensional variabilities of incoming fuselages. To realize fuselage shape adjustment, actuators are used to pull or push several points on a fuselage. Given a fixed number of actuators, the locations of actuators on a fuselage will impact on the effectiveness of shape control. Thus, it is important to determine the optimal placement of actuators in the fuselage shape control problem. In current practice, the actuators are placed with equal distance along the edge of a fuselage without considering its incoming dimensional shape. Such practice has two limitations: (1) it is non-optimal and (2) larger actuator forces may be applied for some locations than needed. This paper proposes an optimal actuator placement methodology for efficient composite fuselage shape control by developing a sparse learning model and corresponding parameter estimation algorithm. The case study shows that our proposed method achieves the optimal actuator placement for shape adjustments of the composite fuselage.

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Retrieval of the optical depth and vertical distribution of particulate scatterers in the atmosphere using O<sub>2</sub> A- and B-band SCIAMACHY observations over Kanpur: a case study

Atmospheric Measurement Techniques ◽

10.5194/amt-5-1099-2012 ◽

2012 ◽

Vol 5 (5) ◽

pp. 1099-1119 ◽

Cited By ~ 38

Author(s):

S. Sanghavi ◽

J. V. Martonchik ◽

J. Landgraf ◽

U. Platt

Keyword(s):

Particulate Matter ◽

Vertical Distribution ◽

Optical Thickness ◽

Vertical Profile ◽

Seasonal Pattern ◽

Computational Cost ◽

Real Data ◽

Estimation Algorithm ◽

Combined Use

Abstract. Due to the well-defined vertical profile of O2 in the atmosphere, the strong A-band (757–774 nm) has long been used to estimate vertical distributions of aerosol/cloud from space. We extend this approach to include part of the O2 B-band (684–688 nm) as well. SCIAMACHY onboard ENVISAT is the first instrument to provide spectral data at moderate resolution (0.2–1.5 nm) in the UV/VIS/NIR including both the O2 A- and B-bands. Using SCIAMACHY specifications, we make combined use of these bands in an optimal estimation algorithm. Theoretical studies show that our algorithm is applicable both over bright and dark surfaces for the retrieval of a lognormal approximation of the vertical profile of particulate matter, in addition to its optical thickness. Synthetic studies and information content analyses prove that such a combined use provides additional information on the vertical distribution of atmospheric scatterers, attributable to differences in the absorption strengths of the two bands and their underlying surface albedos. Due to the high computational cost of the retrieval, we restrict application to real data to a case study over Kanpur through the year 2003. Comparison with AERONET data shows a commonly observed seasonal pattern of haziness, manifesting a correlation coefficient of r = 0.92 for non-monsoon monthly mean AOTs. The retrieved particulate optical thickness is found to be anti-correlated with the relative contrast of the Lambertian equivalent reflectivity (LER) at 682 nm and 755 nm by a coefficient of 0.788, confirming the hypothesis made in Sanghavi et al. (2010). Our case study demonstrates a stable physics-based retrieval of particulate matter using only SCIAMACHY data. The feasibility of our approach is enhanced by the information provided by measurements around the O2 B-band in addition to the A-band. Nonetheless, operational application to SCIAMACHY data remains challenged by radiometric uncertainties, yielding simultaneous retrieval of particle microphysical parameters impracticable and leading to over-reliance on climatological data. Addressing these issues in future instruments similar to SCIAMACHY, coupled with computational resources and speed-up of the current line-by-line radiative transfer calculations, can allow our approach to be extended to the global scale, particularly as it is not limited to dark surfaces.

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Design of an Error Estimation Algorithm for Time Series Data Prediction in Attitude Controlled Systems

INCAS BULLETIN ◽

10.13111/2066-8201.2021.13.3.12 ◽

2021 ◽

Vol 13 (3) ◽

pp. 141-148

Author(s):

M. RAJA ◽

Kokila VASUDEVAN ◽

Kartikay SINGH ◽

Aishwerya SINGH ◽

Ayush GUPTA

Keyword(s):

Error Estimation ◽

Time Series Data ◽

Estimation Algorithm ◽

Series Data ◽

Controlled Systems ◽

Data Prediction ◽

Regression Techniques ◽

Linear Plot ◽

The Stability

This research presents an error estimation approach with the combination of traditional multilevel techniques used to minimize errors for an accurate prediction and to investigate the behavior of such an algorithm for a satellite. The traditional techniques mentioned above are a combination derived from multiple regression techniques and perform a case study for data analysis. A linear plot can easily be predicted, however if a system tends to deviate toward non-linearity the overall result derived from such an algorithm can be non-reliable since each value would depict a completely different output at different levels. The stability of the fixed regression derived is used to determine the accuracy of the system.

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Design and Development of MEMS Sensors Based Inertial Navigation Systems for Aerial Vehicles: A Case Study

International Journal of Sensors Wireless Communications and Control ◽

10.2174/2210327909666190409124143 ◽

2020 ◽

Vol 10 (2) ◽

pp. 179-188

Author(s):

Amanpreet Kaur ◽

Archana Mantri ◽

Vipan Kumar

Keyword(s):

Degrees Of Freedom ◽

Low Cost ◽

Inertial Navigation ◽

Estimation Algorithm ◽

Navigation Systems ◽

Mems Sensors ◽

Fusion Algorithm ◽

Aerial Vehicles ◽

Orientation Information

Background & Objective: MEMS sensors are rapidly growing as a sensing technology in all spheres of science and engineering. MEMS technology is playing an important role in avionics for miniaturization of systems and MEMS based Inertial Navigation System (INS) is one of the example. The situational awareness and performance of an aerial vehicle is computed with the help of an INS. This paper describes the case study for design of MEMS based low cost rugged INS for aerial vehicles. The 9 Degrees of Freedom (DOF) that are obtained from the sensors provide an inaccurate attitude information of aerial vehicles due to presence of external accelerations and the gyroscopic drifts in MEMS sensors. In order to overcome such problems and for the precise and reliable computation of orientation information, the error characteristics of accelerometers, magnetometers and gyroscopes have been combined into a sensor fusion algorithm with ‘Kalman Filter’ to compute the accurate orientation information. The processing has been done on STM32F407VGT6 microcontroller board. An accuracy of ± 0.1 degrees is achieved for Roll and Pitch and ± 1.0 degrees for Yaw have been obtained. The experimental results have been obtained in statically (keeping the device in a static position) and dynamically (rotating the device at different angles along roll, pitch and yaw axis) at room temperature of 22°C. Methods: The design is different in a way that it has used a unique combination of trio MEMS sensors network consisting of FXOS8700CQ Accelerometer, FXAS21000 Gyroscope, FXOS8700CQ Magnetometer. Results: The attitude estimation algorithm has been implemented on the 32-bit microcontroller. The information data is processed and displayed on 88.9 mm TFT-LCD through Graphical User Interface (GUI).

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Case Study on Privacy-Aware Social Media Data Processing in Disaster Management

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9120709 ◽

2020 ◽

Vol 9 (12) ◽

pp. 709

Author(s):

Marc Löchner ◽

Ramian Fathi ◽

David Schmid ◽

Alexander Dunkel ◽

Dirk Burghardt ◽

...

Keyword(s):

Social Media ◽

Disaster Management ◽

Group Discussion ◽

Estimation Algorithm ◽

Stream Data ◽

Social Media Data ◽

Analysis Process ◽

Challenges And Opportunities ◽

Media Data

Social media data is heavily used to analyze and evaluate situations in times of disasters, and derive decisions for action from it. In these critical situations, it is not surprising that privacy is often considered a secondary problem. In order to prevent subsequent abuse, theft or public exposure of collected datasets, however, protecting the privacy of social media users is crucial. Avoiding unnecessary data retention is an important question that is currently largely unsolved. There are a number of technical approaches available, but their deployment in disaster management is either impractical or requires special adaption, limiting its utility. In this case study, we explore the deployment of a cardinality estimation algorithm called HyperLogLog into disaster management processes. It is particularly suited for this field, because it allows to stream data in a format that cannot be used for purposes other than the originally intended. We develop and conduct a focus group discussion with teams of social media analysts. We identify challenges and opportunities of working with such a privacy-enhanced social media data format and compare the process with conventional techniques. Our findings show that, with the exception of training scenarios, deploying HyperLogLog in the data acquisition process will not distract the data analysis process. Instead, several benefits, such as improved working with huge datasets, may contribute to a more widespread use and adoption of the presented technique, which provides a basis for a better integration of privacy considerations in disaster management.

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Cooperative parameter estimation of a nonuniform payload by multiple quadrotors

Robotica ◽

10.1017/s0263574721001272 ◽

2021 ◽

pp. 1-20

Author(s):

Farhad Arab ◽

Farzad A. Shirazi ◽

Mohammad Reza Hairi Yazdi

Keyword(s):

Attitude Control ◽

Equations Of Motion ◽

Estimation Algorithm ◽

Adaptive Controller ◽

Dynamic Equations ◽

Physical Parameters ◽

Constraint Forces ◽

Outer Loop ◽

Simulation Results

Abstract Thispaper addresses the problem of carrying an unknown nonuniform payload by multiple quadrotor agents. The load is modeled as a rigid body with unknown weight and position of Center of Gravity (CG) for the agents, and is included in their dynamic equations of motion. The agents and the load are assumed to be connected to each other by taut ropes. The Udwadia–Kalaba equation is used to calculate the constraint forces on the ropes acting on each quadrotor. Inner-loop and outer-loop controllers for quadrotors position and attitude control are presented. For the outer loop, an estimation algorithm based on the invariance and immersion adaptive control is utilized to estimate the unknown physical parameters of the payload including mass and CG position without using multi-axes force/torque sensors. The inner-loop controller employs an adaptive controller. Simulation results, for two and four agents carrying a nonuniform rod and cubic payload, show the effectiveness of the proposed algorithm. A case study is also performed to investigate the effect of quadrotors positioning on flight endurance of the cooperative aerial team carrying a nonuniform payload.

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