Consideration of signal to noise ratio for an imaging bolometer for ITER

Peterson, B.J.; Reichle, R.; Pandya, Santosh P.; O’Mullane, M.; Mukai, K.

doi:10.1063/5.0043201

Cited by 4 publications

(8 citation statements)

References 8 publications

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“…In contrast to the resistive bolometers, the IRVBs use a tangential view and invoke the toroidal symmetry of the tokamak geometry to provide lines of sight viewing the entire plasma crosssection [14]. In previous work [15] the signal to noise ratio and foil thickness were considered for a single IRVB of arbitrary location viewing the entire plasma cross-section with a tangential view in ITER, assuming a foil viewing the plasma with no collimation for the estimate of the necessary foil thickness. In this work we have designed two IRVBs for ITER taking into consideration the fields of view, necessary foil thicknesses, sensitivities, and nuclear heating of the IRVB foil.…”

Section: Jinst 17 P06034mentioning

confidence: 99%

“…In this work we have designed two IRVBs for ITER taking into consideration the fields of view, necessary foil thicknesses, sensitivities, and nuclear heating of the IRVB foil. In contrast to the previous work [15], we use realistic IRVB locations having the same aperture coordinates as existing IR thermal imaging diagnostic designs and determine the necessary foil thickness for each IRVB detector, including the effect of collimation. In this paper, in section 2 we introduce the two IRVBs, one having a tangential view of the entire cross-section and one having a view looking down into the divertor.…”

Section: Jinst 17 P06034mentioning

confidence: 99%

“…In a previous work, the necessary foil thickness was estimated by assuming the foil was exposed to the entire plasma without collimation [15]. This method however should result in an underestimation of the foil thickness.…”

Section: Determination Of Necessary Foil Thicknesses and Estimation O...mentioning

confidence: 99%

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Estimates of foil thickness, signal, noise, and nuclear heating of imaging bolometers for ITER

Peterson¹,

Nishitani²,

Reichle³

et al. 2022

J. Inst.

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Imaging bolometers have been studied for ITER to serve as a complementary diagnostic to the resistive bolometers for the measurement of radiated power. Two tangentially viewing InfraRed imaging Video Bolometers (IRVB) could be proposed for an ITER equatorial port, one having a view of the entire plasma cross-section (core viewing) and one tilted down 43 degrees from the horizontal to view the divertor (divertor viewing). The IRVBs have 7 cm (horizontal) by 9 cm (vertical) Pt sensor foils, 6 mm × 6 mm apertures, 15 × 20 pixels and focal lengths of 7.8 cm and 21 cm, respectively. Using SANCO and SOLPS models for a 840 m3 plasma radiating 67.3 MW, synthetic images from the IRVBs are calculated to estimate the maximum signal strengths to be 246 W/m2 and 62 W/m2, respectively. We propagate the X-ray energy spectra from the models through the synthetic diagnostics to give the photon energy spectrum for each IRVB pixel, which are used to calculate the fraction of the power absorbed by the foil as a function of foil thickness. Using a criteria of >95% absorbed power fraction, we selected foil thicknesses of 30 μm and 10 μm, respectively. We used these thicknesses and assumed IR systems having 105 fps, 1024×1280 pixels and sensitivities of 15 mK, to calculate the IRVB sensitivities of 3.19 W/m2 and 1.05 W/m2, and signal to noise ratios of 77 and 59, respectively. Using the Monte Carlo Nuclear Particle code we calculated for the core viewing IRVB the foil heating by neutrons to be 1.0 W/m2 and by gammas to be 117 W/m2. This indicates that countermeasures may be needed to remove the nuclear heating signal.

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Section: Jinst 17 P06034mentioning

confidence: 99%

Section: Jinst 17 P06034mentioning

confidence: 99%

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Estimates of foil thickness, signal, noise, and nuclear heating of imaging bolometers for ITER

Peterson¹,

Nishitani²,

Reichle³

et al. 2022

J. Inst.

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“…When the noise component is less, the SNR is larger, and the effect of the SR system is better. The SNR output can be explained as follows [45][46][47]…”

Section: System Measurement Indexmentioning

confidence: 99%

A Novel Advancing Signal Processing Method Based on Coupled Multi-Stable Stochastic Resonance for Fault Detection

et al. 2021

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In recent years, methods for detecting motor bearing faults have attracted increasing attention. However, it is very difficult to detect the faults from weak motor bearing signals under the strong noise. Stochastic resonance (SR) is a popular signal processing method, which can process weak signals with the noise, but the traditional SR is burdensome in determining its parameters. Therefore, in this paper, a new advancing coupled multi-stable stochastic resonance method, with two first-order multi-stable stochastic resonance systems, namely CMSR, is proposed to detect motor bearing faults. Firstly, the effects of the output signal-to-noise ratio (SNR) for system parameters and coupling coefficients are analyzed in-depth by numerical simulation technology. Then, the SNR is considered as the fitness function for the seeker optimization algorithm (SOA), which can adaptively optimize and determine the system parameters of the SR by using the subsampling technique. An advancing coupled multi-stable stochastic resonance method is realized, and the pre-processed signal is input into the CMSR to detect the faults of motor bearings by using Fourier transform. The faults of motor bearings are determined according to the output signal. Finally, the actual vibration data of induction motor bearings are used to prove the effectiveness of the proposed CMSR. The comparison results with the MSR show that the CMSR can obtain a higher output SNR, which is more beneficial to extract weak signal features and realize fault detection. At the same time, this method also has practical application value for engineering rotating machinery.

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“…Sawangjai et al [ 3 ] experimented by generative adversarial network approach for removing ocular artifact from EEG signal with a moderate sensitivity. Similarly, Peterson et al [ 4 ] reviewed towards signal-to-noise ratio for an ITER. A model using combined methods of wavelet-ICA and SVM has proposed by author [ 5 ] to improve the elimination process of artifacts without any loss of data in EEG signals and without depending on any thresholding function.…”

Section: Introductionmentioning

confidence: 99%

Recognition of Ocular Artifacts in EEG Signal through a Hybrid Optimized Scheme

Sahoo

Mohapatra²

2022

BioMed Research International

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Brain computer interface (BCI) requires an online and real-time processing of EEG signals. Hence, the accuracy of the recording system is improved by nullifying the developed artifacts. The goal of this proposal is to develop a hybrid model for recognizing and minimizing ocular artifacts through an improved deep learning scheme. The discrete wavelet transform (DWT) and Pisarenko harmonic decomposition are used for decomposing the signals. Then, the features are extracted by principal component analysis (PCA) and independent component analysis (ICA) techniques. After collecting the features, an optimized deformable convolutional network (ODCN) is used for the recognition of ocular artifacts from EEG input signals. When artifacts are sensed, the moderation method is executed by applying the empirical mean curve decomposition (EMCD) followed by ODCN for noise optimization in EEG signals. Conclusively, the spotless signal is reconstructed by an application of inverse EMCD. The proposed method has achieved a higher performance than that of conventional methods, which demonstrates a better ocular artifact reduction by the proposed method.

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Consideration of signal to noise ratio for an imaging bolometer for ITER

Cited by 4 publications

References 8 publications

Estimates of foil thickness, signal, noise, and nuclear heating of imaging bolometers for ITER

Estimates of foil thickness, signal, noise, and nuclear heating of imaging bolometers for ITER

A Novel Advancing Signal Processing Method Based on Coupled Multi-Stable Stochastic Resonance for Fault Detection

Recognition of Ocular Artifacts in EEG Signal through a Hybrid Optimized Scheme

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