Effective Noise Cancellation Research Articles

Digital Active EMI Filter for Smart Electronic Power Converters

Electronic power converters are widespread and crucial components in modern energy scenarios. Beyond mere electrical energy conversion, their electronic structure allows several functionalities to be naturally embedded in them, including energy management, diagnosis, communication, etc. The operation of the converter itself, or the system interfaced by the same, commonly produces undesired electromagnetic interferences (EMIs) that should comply with prescribed limits. This paper presents a digital active EMI filter designed to mitigate such disturbances. The proposed hardware implementation can acquire and analyze the common-mode (CM) noise affecting the circuit and inject a compensation signal to attenuate the measured interference. A novel adaptive algorithm is introduced to compute the necessary signals for effective noise cancellation. The implementation is integrated within a single printed circuit board interfaced with a field-programmable gate array (FPGA) running the control algorithm. The digital filter’s efficacy in EMI reduction is demonstrated using a synchronous buck converter with gallium nitride (GaN) power devices, achieving significant noise reduction. Additionally, potential functionalities are envisioned to fully exploit the capabilities of the proposal beyond EMI filtering, like fault detection, predictive maintenance, smart converter optimization, and communication.

A Current Noise Cancellation Method Based on Fractional Linear Prediction for Bearing Fault Detection.

The stator current in an induction motor contains a large amount of information, which is unrelated to bearing faults. This information is considered as the noise component for the detection of bearing faults. When there is noise information in the current signal, it can affect the detection of motor bearing faults and lead to the possibility of false alarms. Therefore, to accomplish an effective bearing fault detection, all or some of these noise components must be properly eliminated. This paper proposes the use of fractional linear prediction (FLP) as a noise elimination method in bearing fault diagnosis, which makes these noise components the predictable components and this bearing fault information the unpredictable components. The basis of the FLP is to eliminate noise components in the current signal by predicting predictable components through linear prediction theory and optimal prediction order. Meanwhile, this paper adopts the FLP model with limited memory samples. After determining the optimal number of memories, only the fractional derivative order parameter needs to be optimized, which greatly reduces the computational complexity and difficulty in parameter optimization. In addition, this paper uses spectral analysis of the current signals through experimental simulation to compare the FLP method with the linear prediction (LP) method and the time-shifting (TS) method that have been successfully applied to bearing fault diagnosis. Based on the analysis results, the FLP method can better extract fault features and achieve better bearing fault diagnosis results, verifying the effectiveness and superiority of the FLP method in the field of bearing fault diagnosis. Additionally, the predictive performance of thevFLP and LP was compared based on experimental data, verifying the advantages of the FLP method in predictive performance, indicating that this method has a better noise cancellation effect.

Denoising complex background radar signals based on wavelet decomposition thresholding

Abstract The echo signals of the radar in complex backgrounds are often very unstable and thus require effective noise cancellation. In this paper, according to the characteristics of continuous wavelet variation and discrete wavelet variation, the decomposition effect of multi-resolution analysis and orthogonal Mallat algorithm on low-frequency and high-frequency non-smooth signals is studied, and the selection method of wavelet bases is explored. Then, the noise characteristics affecting the pulsed LIDAR system are analyzed, and the LIDAR pulse signal is simulated by MATLAB, while Gaussian white noise is introduced to obtain the noise-added echo signal, and then multiple wavelet threshold denoising methods are applied to denoise the echo signal. For the input signal-to-noise ratio of −10.57 dB, the output signal-to-noise ratios of db8, db9, db10, and bior3.5 wavelet bases under forced thresholding are −1.971, −2.178, −2.173, and −1.032, respectively. For different input signal-to-noise ratios, the average root mean square error of db8, db9, db10, and bior3.5 wavelet bases under default thresholding is 1.51. The denoising methods for radar signals using the properties of wavelet decomposition have obvious superiority compared to traditional filters, and the wavelet transforms threshold denoising methods have wide adaptability.

Improved Variable Step Size Least Mean Square Algorithm for Pipeline Noise

In this study, we employ the active noise control (ANC) method to eliminate the low-frequency part of the noise generated by the rotation of the axial fan in heating, ventilation, and air-conditioning (HVAC) pipelines. Because the traditional variable step size least mean square (VSS-LMS) algorithm has poor tracking performance, we propose a variable step size filtered-X least mean square (FXLMS) algorithm based on the arctangent function to improve the adaptive filtering method of the convergence speed and noise cancellation effect. The step size of the proposed algorithm can be adjusted according to the error. When the error signal is significant, a larger step can be obtained, and when the error is small, the step size smoothness of the algorithm can be optimized. Compared with the traditional VSS-LMS algorithm, the convergence speed of the proposed algorithm is increased by 29%, the noise reduction effect is enhanced by 19%, and the mean square error (MSE) is reduced by 23% (0.0084). In addition, we developed a hardware experimental platform based on noise characteristics. In the noise reduction test using a GB/T 5836.2-06 standard PVC pipeline, the system reduced the noise by 12–17 dB.

Simulation of LMS based adaptive noise cancellation using Labview

The audio signals processed in the signal measurement systems are inevitably susceptible to unwanted noise which significantly affects the quality of the signal and the overall performance of the signal communication systems. Due to its' random and unpredictable nature, the amount of noise in signals has proven to be a significant issue in designing these systems and recently has been a trending research topic. In this regard, the active noise cancellation method has proven to be an effective technique for eliminating the noise effects on signal processing. The concept of active noise cancellation is based on the application of adaptive filters and algorithms proposed to reduce the signal corruption and distortion caused by the noise due to the principle of destructive interference. In this paper a simulation model of active noise reduction technique using the LMS (Least Mean Square) algorithm in Labview is presented. The purpose of the work is to investigate the noise cancellation effect on a recorded audio file in terms of analyzing the audio file before and after filtering out the noise by using the LMS algorithm and discuss the results thereof.

A novel and integrated architecture for identification and cancellation of noise from GSM signal

There are multiple reasons for the evolution as well as the presence of noise over transmitted GSM signal. In spite of various approaches towards noise cancellation techniques, there are less applicable techniques for controlling noise in acoustic GSM signal. Therefore, the proposed manuscript presents an integrated modelling which performs modelling of noise identification that could significantly assist in successful noise cancellation. The proposed system uses three different approach viz. i) stochastic based approach for noise modelling, ii) analytical-based approach where allocated power acts as one of the prominent factors of noise, and iii) wavelet-based approach for effective decomposition of GSM signal for assisting better noise cancellation technique followed by better retention of signal quality. Simulated in MATLAB, the study outcome shows that it offers a cost-effective implementation, A Practical Approach for Noise identification, and Effective Noise Cancellation with Signal quality retention. The proposed system offers approximately 24% of enhancement in noise reduction as compared to any existing digital filters with 1.6 seconds faster in processing speed.

Muffler structure improvement based on acoustic finite element analysis

Aiming to obtain the acoustic attenuation performance of exhaust muffler of diesel engine and the influence of main structural parameters on its acoustic attenuation characteristics, the finite element analysis method and acoustic theory were adopted to numerically investigate the acoustic attenuation performance under the boundary condition of acoustic adiabatic propagation and muffler wall. It suggested that the noise cancellation effect of muffler was poor at the middle and low frequency in range of 0–3000 Hz, and the transfer loss of muffler was basically 0 dB pass frequency at 1100 Hz. According to previous single-factor study experience, the structural factors, such as the expansion ratio, insertion length of outlet perforated pipe, the distance between the diaphragm and the front part of muffler, have influences on the acoustic performance of muffler at low frequency. Thus, they were taken as the starting point to study the influence of multiple interaction factors on the muffling performance by using orthogonal design method combined with the finite element analysis method. The influence degree of different structure parameters on the acoustic performance of muffler and the optimized structure parameters were obtained. Through the analysis on the acoustic characteristic of the optimized muffler, it indicated that the transmission loss of the improved muffler had significant increase in other frequency range except the range of 650–800 Hz and 2500–2700 Hz, especially at frequency of 1100 Hz compared with the original muffler. In the range of 0–3000 Hz, the mean of transmission loss of the improved muffler was about 9.8 dB larger than that of original muffler, which indicated that better noise cancellation effect was achieved. The improved muffler also provided a certain reference for the structural improvement of similar muffler.

Advanced digital signal processing methods for effective noise cancellation of vehicle related signals. State of the Art

The current trend of vehicle technology’s evolution points towards a further automation of the automobile. The information that such a vehicle processes and handles becomes therefore more important from the performance but also from the safety point of view. The main target of this research is to improve the reliability, accuracy and timing of the information measured by mass produced sensors, whether the sensors are set up in single or array configuration. The scope of the considered sensors covers those related to the automotive sector, both current and potential ones. It is planned to achieve the main target by 1) actively reducing the noise to increase the SNR of the sensor measurements and/or by 2) using advanced processing methods that remove/minimize the delay they introduce in the processing system.

CONTROL AND ESTIMATION OF BIOLOGICAL SIGNALS (ECG) USING ADAPTIVE SYSTEM

In this paper, we present a simple and efficient adaptive noise removal technique for de-noising the (ECG) signal. There are different techniques earlier used for de-noising the ECG signal ,adaptive filtration like least mean square (LMS), NLMS, BLMS , etc. In this paper we used recursive least square technique for adaptive filtration. The power line noises have been implemented according to their basic properties. After that, these noises have been mixed with ECG signal and nullify these noises using the LMS,NLMS and the RLS algorithms. Finally a performance study has been done between these algorithms based on their parameters and also discussed the effect of filter length and the corresponding signal to noise ratio. Results indicate that the noises cannot be handled by the LMS filtering whereas the RLS can handle these types of noises. Furthermore, most of the cases the RLS has achieved best effective noise cancellation performance although its computation time is slightly high. We are using the RLS Algorithm by matlab for simulation.

The geological Hubble: A reappraisal for shallow water

Traditional two-dimensional (2D) seismic acquisition techniques image the subsurface using a grid of orthogonal lines. Dips are recorded only in the along-track direction, limiting migration to a 2D along-track approximation of the inherently 3D wavefields. This produces profiles that are often complicated by out-of-plane reflections and with resolution (for structural interpretation) constrained by the line spacing rather than the source wavelength. The acquisition of true 3D seismic reflection data, in contrast, provides dip information for the reflected wavefields in both along- and across-track directions. This allows a full treatment of the 3D wavefields during migration, affording accurate 3D structural reconstruction, significantly improved resolution (theoretically 1/2 source wavelength), and increasing signal-to-noise ratio (SNR) through more effective noise cancellation.

The dynamics of monolithic suspensions for advanced detectors: A 3-segment model

In order to reduce the suspension thermal noise, the second generation GW interferometric detectors will employ monolithic suspensions in fused silica to hold the mirrors. The fibres are produced by melting and pulling apart a fused silica rod, obtaining a long thin wire with two thicker heads. The dynamics of such a fibre is in principle different from that of a cylindrical, regular fibre, because most of the deformation energy is stored in the neck region where the diameter is variable. This is an advantage, since adjusting the neck tapering, a thermoelastic noise cancellation effect can be obtained. Therefore, a careful study of the suspensions behavior is necessary to estimate the overall noise and to optimize the control strategy. To simplify the control design, a simple three segment model for the silica fibres has been developed, fully equivalent to the beam equation at low frequencies. The model, analytically proved for a regular cylindrical fibre, can be extended to a fibre with tapered necks, provided that the equivalent bending length is suitably measured. We developed a tool to measure the position of the bending point for each fibre, thus allowing to experimentally check the validity of the model. A numerical code has been written to solve the beam equation for wires with varying diameter. This code confirms the validity of the three segment model. Moreover, it is possible to extend the solution to higher frequencies thus computing the transfer function and the energy distribution of the suspension system and estimating the thermal noise contribution.

Single Polarization-Mode-Beating Frequency Fiber Laser

We demonstrate a single-frequency fiber laser cavity that allows for measuring changes in the relative phase of two independent orthogonal polarization modes. Longitudinal-mode selection is carried out by a matched-pair of fiber Bragg gratings in a Fabry-Perot configuration and an intracavity polarizing beam splitter allows for adjustments on each polarization independently. The polarization-mode-beating signals generated with this laser are stable over long periods of time, owing to the noise cancellation effect achieved by the common cavity shared by both polarizations. This heterodyne detection scheme allows for measuring changes in frequency as small as 5 kHz, or equivalently, wavelength changes of 40 am (attometers) which are practically impossible to resolve in the wavelength domain. The proposed configuration has possible significance as an ultrasensitive and stable polarimetric optical fiber sensor.

Improved Tactical Headset: The Effect of Noise Cancellation on Sound Localization

Among other dangers, soldiers in combat often risk hearing damage. A new source of damage is an increase in crew compartment noise resulting from the addition of armored protection to Highly Mobile Multi-Wheeled Vehicles (HMMWVs, commonly known as “Humvee”). To protect soldiers, the US Army may replace the current Interim Headset (IH) with an Improved Tactical Headset (ITH), which uses noise cancellation technology. However, decision makers are concerned that the ITH may affect perception. In the current study, twenty-one soldiers were tested for accuracy of sound localization in an 8 times 2 mixed experimental design (Speaker Location x Headset Type). Results indicate soldiers wearing either headset experienced the front/back confusion typically found in the literature; but soldiers wearing the ITH localized sound more accurately when the sounds originated from their rear and right rear. These findings may support the ITH as the preferred intervention.

Hybrid neuro-fuzzy filter for impulse noise removal

A new filter is presented for images which are highly corrupted by impulse noise. The proposed operator is based on a hybrid neuro-fuzzy approach. The network structure of the filter is specifically designed to detect different patterns of noisy pixels typically occurring in highly corrupted data. The fuzzy mechanism embedded in the network aims at removing noise pulses without destroying fine details and textures. A learning method based on the genetic algorithms is adopted to adjust the network parameters from a set of training data. Experimental results show that the neuro-fuzzy filter is able to yield a very effective noise cancellation and to perform significantly better than state-of-the-art operators in the literature.

Gain and noise in subthreshold longitudinal laser modes.

A theoretical study is presented of the gain profile and noise spectrum in the vicinity of the longitudinal-mode frequency separation of a single-mode laser amplifier of class A or class B. The gain and the noise are associated with the adjacent subthreshold modes on either side of the lasing mode; coupled equations of motion for these three modes have been solved. The amplitudes of the contributions of each individual subthreshold mode to both the gain and the noise are generally anticorrelated. Thus striking cancellation effects should occur in self-heterodyne measurements from the superposition of these contributions. The theoretical predictions are compared with the results of a parallel experimental study on a single-mode argon-ion laser amplifier. Measurements of the gain profiles and noise spectra close to the longitudinal-mode separation are reported for a range of laser output powers. Results are presented for simultaneous detection of the contributions of the two adjacent modes; for detection of only one adjacent mode, the other being suppressed with a Fabry-P\'erot \'etalon; and again for detection of both modes but with their phase relative to the central laser beam modified by a Fabry-P\'erot phase shifter. The predicted cancellation effects are clearly confirmed, and the gain profiles and noise spectra are in good agreement with the theoretical expressions. The noise-cancellation effect is demonstrated by the generation of an optical ``antinoise'' beam that is nearly 180\ifmmode^\circ\else\textdegree\fi{} out of phase with respect to a broadband noisy input beam.

A polarization modulation (PLM)/optical coherent detection system and its phase noise cancelling effect

In coherent optical communication systems, the phase noise of the optical source is the dominant factor in limiting the receiving characteristics and its reduction is required. In this paper, a polarization modulationl optical coherent detection system is proposed and theoretical and experimental studies are carried out for this system. First, it is demonstrated that the polarization modulation signal is a differential phase-modulated optical signal between the two orthogonal polarization components. The fundamental principle for the optical coherent detection system is presented. Next, by taking into account the characteristics of the modulator, a general representation of the polarization modulation optical signals is derived and the inherent characteristics of the present system is shown. Further, for a polarization modulation/optical heterodyne detection system for a long-distance transmission, the detection and demodulation methods are presented. The phase noise cancellation effect is found as well as the fact that the polarization axis matching between the transmitter and the receiver is not necessary if a circular polarization modulation is used. The bit error rate of the polarization modulation/optical heterodyne detection system is analyzed theoretically. By comparing this system with other coherent optical communication systems, the receiving characteristics are evaluated. Finally, fundamental experiments are carried out for the optical heterodyne detection of the polarization modulation signals and the phase noise cancellation effect of the present system is confirmed.