scholarly journals Temporal design for additive manufacturing

2020 ◽  
Vol 106 (9-10) ◽  
pp. 3849-3857
Author(s):  
S. Saliba ◽  
J. C. Kirkman-Brown ◽  
L. E. J. Thomas-Seale
Keyword(s):  
Additive Manufacturing ◽  
Time Domain ◽  
Processing Parameters ◽  
Software Pipeline ◽  
Novel Approach ◽  
Knowledge Propagation ◽  
End Use ◽  
The Time Domain ◽  
And Control ◽  
Design For Am

AbstractAdditive manufacturing (AM) is expected to generate huge economic revenue by 2025; however, this will only be realised by overcoming the barriers that are preventing its increased adoption to end-use parts. Design for AM (DfAM) is recognised as a multi-faceted problem, exasperated by constraints to creativity, knowledge propagation, insufficiencies in education and a fragmented software pipeline. This study proposes a novel approach to increase the creativity in DfAM. Through comparison between DfAM and in utero human development, the unutilised potential of design through the time domain was identified. Therefore, the aim of the research is to develop a computer-aided manufacturing (CAM) programme to demonstrate design through the time domain, known as Temporal DfAM (TDfAM). This was achieved through a bespoke MATLAB code which applies a linear function to a process parameter, discretised across the additive build. TDfAM was demonstrated through the variation of extrusion speed combined with the infill angle, through the axial and in-plane directions. It is widely accepted in the literature that AM processing parameters change the properties of AM materials. Thus, the application of the TDfAM approach offers the engineer increased creative scope and control, whilst inherently upskilling knowledge, in the design of AM materials.

scholarly journals Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jianqin Hang ◽  
Xu Zhang
Keyword(s):  
Time Domain ◽  
Time Varying ◽  
Investor Attention ◽  
Causality Test ◽  
Novel Approach ◽  
Rolling Window ◽  
Causality Tests ◽  
High Volatility ◽  
The Time Domain ◽  
Quantile Causality

This study proposes a novel approach that incorporates rolling-window estimation and a quantile causality test. Using this approach, Google Trends and Bitcoin price data are used to empirically investigate the time-varying quantile causality between investor attention and Bitcoin returns. The results show that the parameters of the causality tests are unstable during the sample period. The results also show strong evidence of quantile- and time-varying causality between investor attention and Bitcoin returns. Specifically, our results show that causality appears only in high volatility periods within the time domain, and causality presents various patterns across quantiles within the quantile domain.

Adding the Human Element to Ship Manoeuvring Simulations

2010 ◽  
Vol 63 (4) ◽  
pp. 695-716 ◽  
Author(s):  
Karl Gunnar Aarsæther ◽  
Torgeir Moan
Keyword(s):  
Time Domain ◽  
Support Functions ◽  
Guidance And Control ◽  
Human Element ◽  
Ship Manoeuvring ◽  
Human Operators ◽  
The Time Domain ◽  
Time Required ◽  
And Control ◽  
The Relationship

Time-domain simulation of ship manoeuvring has been utilized in risk analysis to assess the effect of changes to the ship-lane, development in traffic volume and the associated risk. The process of ship manoeuvring in a wider socio-technical context consists of the technical systems, operational procedures, the human operators and support functions. Automated manoeuvring simulations without human operators in the simulation loop have often been preferred in simulation studies due to the low time required for simulations. Automatic control has represented the human element with little effort devoted to explain the relationship between the guidance and control algorithms and the human operator which they replace. This paper describes the development and application of a model for the human element for autonomous time-domain manoeuvring simulations. The method is applicable in the time-domain, modular and found to be capable of reproducing observed manoeuvre patterns, but limited to represent the intended behaviour.

scholarly journals Power System Stabilizer Tuning Algorithm in a Multimachine System Based on S-Domain and Time Domain System Performance Measures

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5644
Author(s):  
Predrag Marić ◽  
Ružica Kljajić ◽  
Harold R. Chamorro ◽  
Hrvoje Glavaš
Keyword(s):  
Power Systems ◽  
Power System ◽  
Time Domain ◽  
Synchronous Generator ◽  
Pole Placement ◽  
Power System Stabilizer ◽  
Weight Functions ◽  
Novel Approach ◽  
The Time Domain ◽  
System Stabilizer

One of the main characteristics of power systems is keeping voltages within given limits, done by implementing fast automatic voltage regulators (AVR), which can raise generator voltage (i.e., excitation voltage) in a short time to ceiling voltage limits while simultaneously affecting the damping component of the synchronous generator electromagnetic torque. The efficient way to increase damping in the power system is to implement a power system stabilizer (PSS) in the excitation circuit of the synchronous generator. This paper proposes an enhanced algorithm for PSS tuning in the multimachine system. The algorithm is based on the analysis of system participation factors and the pole placement method while respecting the time domain behavior of the system after being subdued with a small disturbance. The observed time-domain outputs, namely active power, speed, and rotor angle of the synchronous generator, have been classified and validated with proposed weight functions based on the minimal square deviation between the initial values in a steady-state and all sampled values during the transitional process. The system weight function proposed in this algorithm comprises s-domain and time-domain indices and represents a novel approach for PSS tuning. The proposed algorithm performance is validated on IEEE 14-bus system with a detailed presentation of the results in a graphical and table form.

scholarly journals Time-Frequency Signal Synthesis and Its Application in Multimedia Watermark Detection

2021 ◽  
Author(s):  
Lam Le
Keyword(s):  
Time Domain ◽  
Chirp Signal ◽  
Time Frequency ◽  
Synthesis Technique ◽  
Polynomial Phase ◽  
Novel Approach ◽  
Signal Synthesis ◽  
Time Frequency Localization ◽  
The Time Domain ◽  
The Individual

A novel approach is proposed in this thesis to synthesize the time domain chirp signal from the joint time-frequency distribution (TFD). The objective is to reconstruct the original signal from its corrupted version. The new signal synthesis technique is based on the Discrete Polynomial Phase Transform (DPPT) and the TFD of the signal to be synthesized. The TFD is used to separate the mono-component signals from a multi-component signal. The DPPT is then applied on the estimated mono-components to have a final synthesized version of the individual time domain signals. The candidate TFD to be used in the synthesis technique is chosen from a group of common TFDs based on their performance with different types of signals. The criteria for the comparison are joint time-frequency localization, low susceptibility to noise, cross-term suppression and the precision of the instantaneous frequency estimated from these distributions. Smoothed Psuedo Wigner-Ville Distribution is chosen as the processing TDFD in the proposed signal synthesis technique. The proposed chirp synthesis technique is applied to detect the presence of the chirp signal embedded as a watermark message in multimedia security applications. The technique can detect the presence of chirp signals from a corrupted chirp with a bit error rate up to signal synthesis is proved to be less than that of the detection method based on the Hough Radon Transform and the proposed signal synthesis technique may also be used as an error correction tool in other applications.

scholarly journals Time-Frequency Signal Synthesis and Its Application in Multimedia Watermark Detection

2021 ◽  
Author(s):  
Lam Le
Keyword(s):  
Time Domain ◽  
Chirp Signal ◽  
Time Frequency ◽  
Synthesis Technique ◽  
Polynomial Phase ◽  
Novel Approach ◽  
Signal Synthesis ◽  
Time Frequency Localization ◽  
The Time Domain ◽  
The Individual

A novel approach is proposed in this thesis to synthesize the time domain chirp signal from the joint time-frequency distribution (TFD). The objective is to reconstruct the original signal from its corrupted version. The new signal synthesis technique is based on the Discrete Polynomial Phase Transform (DPPT) and the TFD of the signal to be synthesized. The TFD is used to separate the mono-component signals from a multi-component signal. The DPPT is then applied on the estimated mono-components to have a final synthesized version of the individual time domain signals. The candidate TFD to be used in the synthesis technique is chosen from a group of common TFDs based on their performance with different types of signals. The criteria for the comparison are joint time-frequency localization, low susceptibility to noise, cross-term suppression and the precision of the instantaneous frequency estimated from these distributions. Smoothed Psuedo Wigner-Ville Distribution is chosen as the processing TDFD in the proposed signal synthesis technique. The proposed chirp synthesis technique is applied to detect the presence of the chirp signal embedded as a watermark message in multimedia security applications. The technique can detect the presence of chirp signals from a corrupted chirp with a bit error rate up to signal synthesis is proved to be less than that of the detection method based on the Hough Radon Transform and the proposed signal synthesis technique may also be used as an error correction tool in other applications.

scholarly journals Suppressing of Power Line Artifact From Electroencephalogram Measurements Using Sparsity in Frequency Domain

2021 ◽  
Vol 15 ◽  
Author(s):  
Jin-Lin Tan ◽  
Zhi-Feng Liang ◽  
Rui Zhang ◽  
You-Qiang Dong ◽  
Guang-Hui Li ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Disease Diagnosis ◽  
Power Line ◽  
Spectral Lines ◽  
Rectangular Window ◽  
Parameter Estimations ◽  
Novel Approach ◽  
The Time Domain ◽  
Spectrum Correction

Electroencephalogram (EEG) plays an important role in brain disease diagnosis and research of brain-computer interface (BCI). However, the measurements of EEG are often exposed to strong interference of power line artifact (PLA). Digital notch filters (DNFs) can be applied to remove the PLA effectively, but it also results in severe signal distortions in the time domain. To address this problem, spectrum correction (SC) based methods can be utilized. These methods estimate harmonic parameters of the PLA such that compensation signals are produced to remove the noise. In order to ensure high accuracy during harmonic parameter estimations, a novel approach is proposed in this paper. This novel approach is based on the combination of sparse representation (SR) and SC. It can deeply mine the information of PLA in the frequency domain. Firstly, a ratio-based spectrum correction (RBSC) using rectangular window is employed to make rough estimation of the harmonic parameters of PLA. Secondly, the two spectral line closest to the estimated frequency are calculated. Thirdly, the two spectral lines with high amplitudes can be utilized as input of RBSC to make finer estimations of the harmonic parameters. Finally, a compensation signal, based on the extracted harmonic parameters, is generated to suppress PLA. Numerical simulations and actual EEG signals with PLA were used to evaluate the effectiveness of the improved approach. It is verified that this approach can effectively suppress the PLA without distorting the time-domain waveform of the EEG signal.

scholarly journals Statistically significant contrasts between EMG waveforms revealed using wavelet-based functional ANOVA

2013 ◽  
Vol 109 (2) ◽  
pp. 591-602 ◽  
Author(s):  
J. Lucas McKay ◽  
Torrence D. J. Welch ◽  
Brani Vidakovic ◽  
Lena H. Ting
Keyword(s):  
Temporal Resolution ◽  
Time Domain ◽  
Statistical Power ◽  
A Priori ◽  
Simulated Data ◽  
High Temporal Resolution ◽  
Novel Approach ◽  
Functional Anova ◽  
The Time Domain ◽  
High Level

We developed wavelet-based functional ANOVA (wfANOVA) as a novel approach for comparing neurophysiological signals that are functions of time. Temporal resolution is often sacrificed by analyzing such data in large time bins, increasing statistical power by reducing the number of comparisons. We performed ANOVA in the wavelet domain because differences between curves tend to be represented by a few temporally localized wavelets, which we transformed back to the time domain for visualization. We compared wfANOVA and ANOVA performed in the time domain (tANOVA) on both experimental electromyographic (EMG) signals from responses to perturbation during standing balance across changes in peak perturbation acceleration (3 levels) and velocity (4 levels) and on simulated data with known contrasts. In experimental EMG data, wfANOVA revealed the continuous shape and magnitude of significant differences over time without a priori selection of time bins. However, tANOVA revealed only the largest differences at discontinuous time points, resulting in features with later onsets and shorter durations than those identified using wfANOVA ( P < 0.02). Furthermore, wfANOVA required significantly fewer (∼¼×; P < 0.015) significant F tests than tANOVA, resulting in post hoc tests with increased power. In simulated EMG data, wfANOVA identified known contrast curves with a high level of precision ( r2 = 0.94 ± 0.08) and performed better than tANOVA across noise levels ( P < <0.01). Therefore, wfANOVA may be useful for revealing differences in the shape and magnitude of neurophysiological signals (e.g., EMG, firing rates) across multiple conditions with both high temporal resolution and high statistical power.

Application of Optimal Input Synthesis to Aircraft Parameter Identification

1976 ◽  
Vol 98 (2) ◽  
pp. 139-145 ◽  
Author(s):  
N. K. Gupta ◽  
R. K. Mehra ◽  
W. E. Hall
Keyword(s):  
Steady State ◽  
Frequency Domain ◽  
Time Domain ◽  
Stability And Control ◽  
Input Design ◽  
Short Period ◽  
Control Derivatives ◽  
The Stability ◽  
The Time Domain ◽  
And Control

This paper considers an application of the Frequency Domain Input Synthesis procedure reference [12] for identifying the stability and control derivatives of an aircraft. In previous studies, the input design has mostly been carried out in the time-domain. However, by using a frequency-domain approach, one can handle criteria that are not easily handled by the time-domain approaches. Numerical results are presented for optimal elevator deflections to estimate the longitudinal stability and control derivatives subject to root-mean square constraints on the input. The applicability of the steady state optimal inputs to finite duration flight testing is investigated. It is shown that the steady state approximation of frequency-domain synthesis is good for data lengths greater than two time cycles for the short period mode of the aircraft longitudinal motions. For data lengths shorter than this, the phase relationships between different frequency components becomes important. The frequency domain inputs are shown to be much better than the conventional doublet inputs.

Sign in / Sign up

Export Citation Format

Share Document