Mode Noise Research Articles

Dual-path coupling V-shaped structure off-axis integrated cavity output spectroscopy (V-OA-ICOS) for water vapor stable isotope detection at 3.66 μm

Residual cavity mode noise and weak output signal are the main factors that restrict the detection performance of off-axis integrated cavity output spectroscopy (OA-ICOS). In order to overcome the above drawbacks, a novel V-shaped off-axis integrated cavity output spectroscopy (V-OA-ICOS) device was demonstrated, and the dual-path coupling method was further proposed. The dual-path coupling V-OA-ICOS device can not only suppress the residual cavity mode noise but also enhance the intensity of the output signal. The V-shaped resonator cavity ensures a more uniform and square-shaped spot pattern distribution on the surface of the highly reflective mirrors, significantly reducing spots overlap. The dual-path coupling method can re-couple the laser reflected by the front cavity mirror, thereby increasing the total energy and mode density of the cavity. The spectrum of water vapor stable isotopes HD16O and H216O at 3.66 μm was measured to illustrate the performance of the presented approach, the dual-path coupling V-OA-ICOS increases the signal-to-noise ratio (SNR) by a factor ∼ 2.1 compared to single path V-OA-ICOS and the signal intensity by a factor of ∼ 2. The δD variation was obtained by measuring the outdoor water vapor isotope using this device for three consecutive days. The variation range of δD is −220‰ ∼ −120‰. This work proposes a new cavity structure and optical re-coupling method, which offers a novel approach to enhance the performance of OA-ICOS devices.

Research on interference compensation methods for color image sensors based on iterative learning

PurposeFixed mode noise and random mode noise always exist in the image sensor, which affects the imaging quality of the image sensor. The charge diffusion and color mixing between pixels in the photoelectric conversion process belong to fixed mode noise. This study aims to improve the image sensor imaging quality by processing the fixed mode noise.Design/methodology/approachThrough an iterative training of an ergoable long- and short-term memory recurrent neural network model, the authors obtain a neural network model able to compensate for image noise crosstalk. To overcome the lack of differences in the same color pixels on each template of the image sensor under flat-field light, the data before and after compensation were used as a new data set to further train the neural network iteratively.FindingsThe comparison of the images compensated by the two sets of neural network models shows that the gray value distribution is more concentrated and uniform. The middle and high frequency components in the spatial spectrum are all increased, indicating that the compensated image edges change faster and are more detailed (Hinton and Salakhutdinov, 2006; LeCun et al., 1998; Mohanty et al., 2016; Zang et al., 2023).Originality/valueIn this paper, the authors use the iterative learning color image pixel crosstalk compensation method to effectively alleviate the incomplete color mixing problem caused by the insufficient filter rate and the electric crosstalk problem caused by the lateral diffusion of the optical charge caused by the adjacent pixel potential trap.

Multi-objective SHM sensor path optimisation for damage detection in large composite stiffened panels

This work proposes a novel methodology for the automatic multi-objective optimisation of sensor paths in structural health monitoring (SHM) sensor networks using archived multi-objective simulated annealing. Using all of the sensor paths within a sensor network may not always be beneficial during damage detection. Many sensor paths may experience significant signal noise, attenuation, and wave mode conversion due to the presence of features, such as stiffeners, and hence impair the detection accuracy of the overall system. Many paths will also contribute little to the overall coverage level or damage detection accuracy of the network and can be ignored, reducing complexity. Knowing which paths to include, and which to exclude, can require significant prior expert knowledge, which may not always be available. Furthermore, even when expert knowledge is considered, the optimum path selection might not be achieved. Therefore, this work proposes a novel automatic procedure for optimising the sensor paths of an SHM sensor network to maximise coverage level, maximise damage detection accuracy and minimise the overall signal noise in the network due to geometric features. This procedure was tested on a real-world large composite stiffened panel with many geometric features in the form of frames and stiffeners. Compared to using all of the available sensor pairs, the optimised network exhibits superior performance in terms of detection accuracy and overall noise. It was also found to provide very similar performance, in terms of coverage level and overall signal noise, to a sensor path network designed based on prior expert knowledge but provided up to 35% higher damage detection accuracy. As a result, the novel procedure proposed in this work has the capability to design high-performing SHM sensor path networks for structures with complex geometries but without the need for prior expert knowledge, making SHM more accessible to the engineering community.

Shielding Effectiveness of HV-HF Transformer for Accelerator Applications

High-voltage high-frequency transformers are employed in DC accelerators. The high frequency produced by the inverter at lower voltage is stepped up to several tens of kilovolts using step-up transformers. These transformers are subjected to high-frequency transients from high-voltage multiplier columns. Electrostatic shielding is very effective in common mode noise reduction. However, in accelerator applications, shielding effectiveness obtained using conductive shields is found compromised in practice. This paper investigates the reasons behind this phenomenon and explores remedial measures.

New generation B-Field and RAD-tolerant DC/DC power converter for on-detector operation

The increase in the number of readout channels in new detectors, like the Micro Pattern Gas Detectors (MPGD), in the order of several millions, requires a large amount of electrical power to supply the front-end electronics, up to hundreds kW. If this power is generated at long distances from the detector, the voltage drop on the connection cables puts serious constraints to the supply current, to the wire cross-section and to the power distribution. A large amount of voltage drop on the cables, apart an increased power dissipation on wire resistance, determines regulation issues on the load in case of current transients. To mitigate these problems, a new generation DC/DC converter, working in a heavily hostile environment and with a power density greater than 200 W/dm3, was developed. It is modular, with up to four independent modules, eight channels each, collected in a water-cooled crate, and can supply the load with an adjustable 10 to 12 V output up to 170 W per channel. In this contribution, the design constraints of such a converter are analysed, taking as a basis the environmental, electrical and mechanical requirements of the ATLAS New Small Wheel (NSW) project. Thermal considerations require the converter to be water-cooled, and the dimensional constraints impose the adoption of an innovative design to convey the dissipated heat towards the heat exchanger. The control and monitoring system allows for the full remote management of the converter. Main electrical parameters were measured and are reported. The converter was also characterized in a harsh working environment, with radiation tests in the CERN CHARM facility beyond the limits estimated for ten years operation in ATLAS, and with magnetic field tests in various orientations, using different magnets at CERN up to 1.3 T. A better common mode noise filtering design improvement was implemented after the first characterization. Final performance measurements after the modifications are also reported.

Feature detection in guided wave ultrasound measurements using simulated spectrograms and generative machine learning

Guided wave ultrasound field measurements capture reflections from aluminothermic welds in the rail track at unknown distances from a transducer. The measured guided wave signals are complex and challenging to interpret due to multiple dispersive modes propagating in the rail, changing environmental conditions, and noise. Data-driven machine learning techniques have been applied to complex signal-processing problems and have shown significant potential in learning and resolving complex problems. This study aims to understand the implications of using various simulated data sets for application within an appropriate learning framework to capture the underlying features of the field measurements and maximise the performance of these techniques. The use of simulated spectrograms, including variations of signal attributes (attenuation, positions of welds, noise, and mode reflection coefficients) generally observed in experimental measurements, allows the reflections of individual modes to be isolated or combined for training. This allows us to present the training data in three distinct forms. The first dataset has the highest mode reflection information density per sample and consists of simulated spectrogram data with multiple reflections of modes from multiple welds, like experimentally obtained spectrograms. The second training dataset consists of spectrograms with multiple mode reflections; however, only for a single weld reflection per spectrogram. The third training set contains a reflection of a single mode from a single weld in each spectrogram. The data-driven models applied are principal component autoregression and variational auto-encoders. The reconstruction error and latent space interpretability were considered as metrics for the algorithms’ ability to learn using test sets, i.e., unseen data. The results show that datasets with sufficient feature variation and higher mode reflection information density better construct the test set of simulated and experimental spectrograms. However, training using the third dataset shows more interpretable latent variables for an artificial growing defect attached to the rail. Furthermore, data-driven machine learning methods trained using simulated spectrogram data are useful for reconstructing and learning features from experimental measurements, provided that the training data have representative mode feature variation and noise.

Analysis of reducing common mode noise of conducted emission in a switching power converter considering parasitic effects

Analysis of reducing common mode noise of conducted emission in a switching power converter considering parasitic effects

Study on effect of charged sand/dust atmosphere on the performance of microwave quantum illumination radar

This paper aims to study the effects of charged sand/dust atmosphere on the performances of microwave quantum illumination (QI) radar. Based on Mie particle scattering theory, using a Monte Carlo method for simulating the physical process which photon is scattered multiple times by discrete random distributed particles, the specific attenuation (dB/km) of microwave propagating in sand/dust atmosphere are analyzed under the conditions of varying atmospheric visibility and sand/dust particles with different charged quantities. It is indicated that the specific attenuation obtained by multiple scattering is smaller than those obtained based on Mie theory, for microwave propagating in charged sand/dust atmosphere. The smaller the atmospheric visibility, the greater the difference, while the difference decreases gradually as the atmospheric visibility increases. Then, it is more reasonable to consider multiple scattering attenuation at lower atmospheric visibility. When sand/dust particle is charged, the specific attenuation is increased, however, this increase is not linear. According to quantum illumination radar theory, a beam splitter-based optical link model is used to simulate the sand/dust atmospheric channel. The effects of charged sand/dust atmosphere with different visibility on the detection error probability, signal-to-noise ratio, and maximum detection range for microwave quantum illumination radar are studied by using quantum radar equation and quantum detection error probability theory. The performances of QI and classical two mode noise (TMN) radar are compared and analyzed. These results show that the performances of quantum illumination radar are improved with increasing sand/dust atmospheric visibility. When sand/dust particle is charged, the performances for QI radar are degraded due to attenuation increase. The change in the performances is nonlinear as the change in sand/dust carrying charge quantity. Increasing the signal frequency can enhance the performance of quantum illumination radar when visibility is high, but when visibility is low, the gain from frequency increase is outweighed by the performance degradation caused by increased attenuation, making it inadvisable to raise the frequency in such cases. The comparison with classical radar reveals that QI radar performs better under the condition of lower atmospheric visibility and lower average photon emission, but this advantage diminishes as the number of photons increases. In a word, these results show that the performances of QI radar are more significant at lower atmospheric visibility. Under higher visibility conditions, the QI system SNR can be improved by increasing frequency. The maximum detection range of the QI radar is significantly better than the classical TMN radar.

Analysis of the bi-bridge topology and power device circuit of the TPS booster dipole power supply

This study primarily discusses a unique topology for constructing a double full bridge circuit. The study establishes a push-pull inverter model and analyses the balance circuit in its architecture. This allows the power supply to initiate the balance circuit and ensures the TPS (Taiwan Photon Source) booster magnet power supply operates smoothly in a safe and balanced voltage region when magnet energy is recovered. We employ the approach of adding Y circuits to mitigate the impact of common mode (CM) noise. Adding a Y circuit effectively suppresses the common-mode noise generation, improving the quality of the output current of the TPS dipole magnet power supply at low currents state and ramping the beam current energy from 150 MeV to 3 GeV. Furthermore, the reproducibility and stability of the injection point can enhance the injection efficiency of the TPS booster magnet power supply. This study presents the results obtained from these efforts.

Passive Cancellation Method for Reduction of Common Mode Noise Currents

Passive Cancellation Method for Reduction of Common Mode Noise Currents

A Dithering Technique for Mitigation of Differential Mode Noise of SiC MOSFET based Buck converter

A Dithering Technique for Mitigation of Differential Mode Noise of SiC MOSFET based Buck converter

A PCB-Incorporated Inductor Based Filter Design Solution for Differential Mode Noise of 3-Phase SiC-MOSFET Based VSI

A PCB-Incorporated Inductor Based Filter Design Solution for Differential Mode Noise of 3-Phase SiC-MOSFET Based VSI

Fully Soft-Switched Buck–Boost Bridgeless PFC Converters With Single-Magnetic Core

This paper proposes new fully soft switched bridgeless buck-boost power factor correction converters using single magnetic core with capability of realizing positive or negative output voltages. Full ZVS operation is provided for the main switches independent of the load and grid voltage variations. Also, the proposed converters have common ground and single ended output which increase power density and alleviates common mode noise. The proposed converters operate under discontinuous conduction mode (DCM) to shape the input current inherently. A 120W, 100kHz laboratory prototype with negative output voltage is implemented to verify the theoretical analysis and the effectiveness of the proposed topologies. The results demonstrate efficiency of 96.2% and total harmonic distortion (THD) of 4% at full load condition.

Production noise on an automated molding line in a foundry

The purpose of the work is to determine the nature of the noise generated during the operation of manual pneumatic rammers, an automated molding line and knockout grids in the foundry shop based on determining the levels of acoustic noise parameters in the mold manufacturing area and ways to reduce their level. To determine the noise parameters, a mode noise spectrum analyzer SL-5868F was used with subsequent digitization of the data obtained on the analyzer. Measurements of noise parameters were carried out at the site for the production of foundry molds with manual pneumatic rammers and an automatic molding line, as well as at the site for knocking out castings on knockout grids. It has been established that the noise generated in the areas of molding and knocking out molds, regardless of the molding method (manual, automatic) and the model of the knockout grid used, is broadband, and there is no homogeneity in the sound field of the generated noise, which is due to the generation of noise from sources characterized by differences in acoustic power levels and the nature of the noise spectrum. The noise from equipment or a technological operation with a shock nature is not constant and has a maximum sound power level in the region of medium and high frequencies generated by the equipment under study. It is possible to reduce the noise level in the foundry shop analyzed in the work by implementing a set of measures to modernize the molding and knocking out equipment or introducing into production an alternative method of manufacturing and knocking out foundry molds, in which, if it is possible to produce castings of a given nomenclature in the required volume with the required level of quality, the above mentioned are excluded and other sources of noise generation of unacceptable levels.

Re-injection off-axis integrated cavity output spectroscopy for the simultaneous detection of N2O, H2O and CO with a mid-infrared QCL laser.

Off-axis integrated cavity output spectroscopy (OA-ICOS) has attracted much interest because it potentially allows highly sensitive field measurements with robust optical alignment. In this paper, a novel instrument that employs a high-finesse optical cavity as an absorption cell has been developed for sensitive measurements of multi-component gases N2O, H2O and CO in the atmosphere based on a mid-infrared quantum cascade laser (QCL) and OA-ICOS. In order to improve the energy utilization and increase the signal-to-noise ratio (SNR) of the signal, a new type of optical path structure of the laser re-injection method is adopted. Furthermore, the system performance can be effectively improved by using a new intervention method of injecting radio frequency (RF) white noise into a laser driver to suppress cavity mode noise and combining the wavelength modulation method (WMS). We compared the sensitivity of the second harmonic signal demodulation between the re-injection method and the standard OA-ICOS, and the SNR increased by 2.68 times compared to the latter. Analysis of the spectral measurements with Allan variance indicates that within an integration time of 1 s, the measurement accuracy of N2O, H2O, and CO is 6.71 ppb, 13.945 ppm, and 1.81 ppb, respectively, and within an integration time of 820 s, the measurement accuracy of N2O, H2O, and CO can be further improved to 1.26 ppb, 2.089 ppm, and 172 ppt, respectively. Our approach represents an underlying analytical method that provides guidelines for monitoring of representative gases in the atmosphere, industrial processes, emergency safety, etc.

Estimating the Differential Mode Noise of a DC-DC Converter

Electromagnetic noise emission is inevitable in a DC-DC converter due to the employed switching technique. In low frequency, the noise propagating through cabling and conductive media is called a conducted emission. A conducted emission consists of differential mode and common mode noise. It is advantageous to know an estimate of emission level for each mode during the design phase so that suitable mitigation can be included earlier.. This paper aims to focus on a method to estimate the differential mode noise emission of a DC-DC converter. The estimation is computed using the input capacitor complex impedance and the current that flows through it. As a study case, a boost and buck converters are used for evaluation. The estimation and measurement results are compared. Despite differences at some frequencies, the estimated and measured results generally agree well. Because of its simplicity, the proposed method can be used as a practical tool in the EMC aspect of DC-DC converter design.

Unsteady drag force on an immersed sphere oscillating near a wall

The unsteady hydrodynamic drag exerted on an oscillating sphere near a planar wall is addressed experimentally, theoretically and numerically. The experiments are performed by using colloidal-probe atomic force microscopy in thermal noise mode. The resonance frequencies and quality factors are extracted from the measurement of the power spectrum density of the probe oscillation for a broad range of gap distances and Womersley numbers. The shift in the resonance frequency of the colloidal probe as the probe goes close to a solid wall infers the wall-induced variations of the effective mass of the probe. Interestingly, a crossover from a positive to a negative shift is observed as the Womersley number increases. In order to rationalize the results, the confined unsteady Stokes equation is solved numerically using a finite-element method, as well as asymptotic calculations. The in-phase and out-of-phase terms of the hydrodynamic drag acting on the sphere are obtained and agree well with the experimental results. All together, the experimental, theoretical and numerical results show that the hydrodynamic force felt by an immersed sphere oscillating near a wall is highly dependent on the Womersley number.

Fault Feature Extraction Method for Rolling Bearings Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Variational Mode Decomposition

Due to the difficulty in dealing with non-stationary and nonlinear vibration signals using the single decomposition method, it is difficult to extract weak fault features from complex noise; therefore, this paper proposes a fault feature extraction method for rolling bearings based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and variational mode decomposition (VMD) methods. CEEMDAN was used to decompose the signal, and the signal was then screened and reconstructed according to the component envelope kurtosis. Based on the kurtosis of the maximum envelope spectrum as the fitness function, the sparrow search algorithm (SSA) was used to perform adaptive parameter optimization for VMD, which decomposed the reconstructed signal into several IMF components. According to the kurtosis value of the envelope spectrum, the optimal component was selected for an envelope demodulation analysis to realize fault feature extraction for rolling bearings. Finally, by using open data sets and experimental data, the accuracy of envelope kurtosis and envelope spectrum kurtosis as a component selection index was verified, and the superiority of the proposed feature extraction method for rolling bearings was confirmed by comparing it with other methods.

Design of sinusoidal-shaped inlet duct for acoustic mode modulation noise reduction of cooling fan

The noise reduction method of installing a sinusoidal-shaped inlet duct on a cooling fan is analyzed theoretically and experimentally in terms of the acoustic mode modulation. Based on Lowson's point force model, the correlation between the free field noise and acoustic mode of the fan rotor and the unsteady forces on the rotor blade surface is established. The azimuthal acoustic mode is demonstrated to partially reflect the composition and intensity of the acoustic source. The theoretical variation in azimuthal acoustic mode indicates that it is possible to completely cancel each mode simultaneously when the phase differences of forces of each order in the secondary source are controlled. A sinusoidal-shaped inlet duct noise reduction structure controlled by a parameter equation is proposed, and the preferred parameter selection is given by the far-field noise measurements. The results of azimuthal mode decomposition exhibit a similar trend to the theoretical analysis. Compared with the straight duct, the chosen sinusoidal-shaped inlet duct achieved greater noise reduction at the blade passing frequency and its first harmonic. The average total sound pressure level in the far field was 6.0 dBA lower than that of the prototype fan, and 1.4 dBA lower than that of the straight duct model.

Dual-band tunable microwave pulse signals generation based on a time domain mode locked optoelectronic oscillator

We propose and experimentally demonstrate a dual-band tunable microwave pulse signals generation method based on a time domain mode locked optoelectronic oscillator (TDML-OEO). The dual-band radio frequency (RF) combs are generated via injecting two single-tone signals and a low frequency signal. The two single-tone signals are injected to optimize the aimed center frequencies gain, while the low frequency signal is used to accomplish the multi-mode oscillation mode locking process. Furthermore, the dual-band RF combs with variable repetition rates of 3.69 MHz, 9.22 MHz, and 18.45 MHz are obtained with an over 72 dB ultra-high suppression of super mode noise as the TDML-OEO operates in the varied harmonic multiples mode locking state. Besides, by adjusting the amplitude and central frequency of the two injected local oscillator signals (LOs), a controllable output power and frequency tunability ranged from 11.1 GHz to 13.8 GHz are achieved for the generated dual-band RF combs. The proposed dual-band tunable microwave pulse generation method has great potential applications in multiband radars and electronic warfare.© 2023 Optica Publishing Group under the terms of the Optica Publishing Group Open Access Publishing Agreement.