Noise Suppression Research Articles

Robust deadbeat predictive current control for unipolar sinusoidal excited SRM with multi-parameter mismatch compensation

In the control of unipolar sinusoidal excited switched reluctance motors (SRMs), deadbeat predictive current controllers (DPCCs) have gained attention for their enhanced dynamic performance. However, periodic disturbances caused by mismatches between the predictive model’s nominal and actual system parameters degrade the control performance of SRMs. To address this issue, a robust DPCC with multi-parameter compensation is proposed to improve dq0-axes current control performance. By analyzing the impact of parameter mismatches, a Kalman filter (KF) is developed to compensate for inductance coefficient mismatches, mitigating periodic disturbances. Additionally, a disturbance estimator with measurement noise suppression is integrated into the DPCC for both state and disturbance estimation to handle residual uncertainties, including winding resistance mismatches, magnetic saturation, and unmodeled dynamics. Compared simulation and experimental results validate the effectiveness of the proposed robust DPCC.

Multi-bandwidth observer-based adaptive robust pressure control for electro-hydraulic brake system with uncertainties and measurement noise

Accurate pressure regulation of electro-hydraulic brake system (EHB) is essential for enhancing braking performance in automobiles. However, component wear and pressure measurement noise can cause model parameters and controlled states to drift, resulting in system chattering. This nonlinear and uncertain state can significantly degrade pressure control performance. Motivated by this, the article presents a controlled state reconstruction-based adaptive robust pressure control technique with noise suppression. Firstly, a reduced dynamics model is established for controller design, which effectively captures the fundamental characteristic of the EHB. Secondly, a multi-bandwidth extended state observer (MBESO) capable of noise suppression is designed to reconstruct controlled states, including unknown disturbances and unmeasured pressure change rates of the EHB. Thirdly, an MBESO-based adaptive robust pressure control technique is introduced, where the control gain and robust factor are updated based on control and observation errors. In addition, the overall performance of the proposed control strategy is analyzed in the frequency domain, and close-loop stability is demonstrated via the Lyapunov method. Finally, the pressure control precision and robustness of the proposed algorithm are validated in both dynamic and static scenarios through sinusoidal and step-response experiments on a hardware-in-loop test bench. The results indicate that the proposed algorithm reduces dynamic pressure-tracking error by up to 62% compared to traditional method under sinusoidal conditions, with steady-state error remaining within 1 bar under step-response conditions.

Characterization of heterodyne optical phase locking for relative laser frequency noise suppression in differential measurement

Characterization of heterodyne optical phase locking for relative laser frequency noise suppression in differential measurement

Integrated noise suppression techniques for enhancing voice activity detection in degraded environments

Integrated noise suppression techniques for enhancing voice activity detection in degraded environments

A non-linear local active noise control with integrated virtual sensing using an adaptive hybrid spline filter

Virtual sensing technique has been a promising means for local active noise control (ANC) to surpass the design constraint of error microphone placement at a desired location. Most existing systems which use virtual sensing employ an finite impulse response (FIR) filter based adaptive filter for achieving noise cancellation. However, the effectiveness of such ANC systems deteriorate in the presence of non-linearities in the system. In this paper, an attempt has been made to develop a class of non-linear ANC systems, with integrated virtual sensing, based on adaptive spline filters. These include a Wiener model, a Hammerstein model and a sandwich Hammerstein-Wiener based hybrid model of non-linear ANC. The learning algorithms for the proposed ANC schemes have been developed and it was observed that the adaptive nature of the activation functions allow the ANC system to shift from linear to non-linear and vice versa depending on the control scenario. The simulation results demonstrate that the hybrid spline based ANC system provides an improved noise reduction performance in non-linear scenarios in comparison with other ANC schemes.

Active noise-cancelling headphones do not improve cognitive performance in office noise environment

Our purpose was to determine the influence of different use settings of on-ear ANC (active noise-cancelling) headphones on performance, experience, and physiological stress in conditions resembling an office where task irrelevant speech is present. Laboratory experiment involved 54 participants, who were exposed to five conditions: 1. No headphones, 2. Headphones without ANC operation, 3. Headphones with ANC operation, 4. Headphones with sound masking playback, 5. Headphones with ANC operation and sound masking playback. In all conditions, speech was present in the room at 52 dB LAeq. Masking was 51 dB LAeq wideband noise played from the headphones. Participants' performance was measured with visual serial recall and 3-back tasks, and physiological stress with heart rate variability. The condition did not influence performances nor physiological stress. The only effects of sound condition were observed in subjective experiences. With masking (conditions 4 and 5), the speech was less annoying than without the headphones (condition 1). Sound environment was estimated to impair performance and disturb concentration less than without the headphones only in condition 5. Therefore, using headphones together with masking and ANC function can improve experience. Using headphones with ANC function alone did not improve performance nor reduce stress level.

Attention-based convolutional neural network for multi-channel active noise control

Multi-channel active noise control systems utilize multiple control units to cancel unwanted noise across different channels simultaneously. By employing adaptive filtering techniques, these systems can effectively reduce noise levels in complex environments, offering improved noise mitigation compared to single-channel active noise control approaches. The disadvantage of adaptive filtering in active noise control is its limited ability to accurately model nonlinearities present in real-world noise environments. In this work, we propose an attention-based convolutional neural network comprising convolutional, deconvolutional, and attention mechanism to approach multi-channel active noise control. The system simultaneously calculates multiple canceling signals to eliminate primary noises captured by error microphones. To evaluate the effectiveness of our proposed model, we conducted testing utilizing filtered white noise spanning various frequency bands. Experimental evaluations across various setups, including different loudspeaker and microphone configurations, as well as variations in secondary source positioning, are used to assess the performance of the proposed approach. Results demonstrate that the proposed attention-based convolutional neural network for multi-channel active noise control yields a noise reduction of 22.65 dB on wideband noise, while the conventional Filtered-x least mean square approach yields a noise reduction of 4.23 dB, indicating the effectiveness of the proposed approach.

A survey of integrating wireless technology into active noise control

Active Noise Control (ANC) is a widely adopted technology for reducing environmental noise across various scenarios. This paper focuses on enhancing noise reduction performance, particularly through the refinement of signal quality fed into ANC systems. We discuss the main wireless technique integrated into the ANC system equipped with some innovative algorithms in diverse environments. Instead of using microphone arrays, which increase the computation complexity of the ANC system, to isolate multiple noise sources to improve noise reduction performance, the application of the wireless technique avoids extra computation demand. Wireless transmissions of reference, error, and control signals are also applied to improve the convergence performance of the ANC system. Furthermore, this paper lists some wireless ANC applications, such as earbuds, headphones, windows, and headrests, underscoring their adaptability and efficiency in various settings.

Analysis of nonminimum phase components of noise control filters in active noise control

In the active noise control (ANC), it is known that the optimal filter becomes a noncausal filter due to the effect of the nonminimum phase components of the secondary path. We have investigated how to make the causal optimal filter by replacing the nonminimum phase components with the frequency components of the primary path. Through the computer simulations, we have confirmed that this filter maintained some noise reduction performance and can be used as a quasi-optimal filter. In this paper, as another approach, we attempt to identify noncausal components using the pre-trained adaptive noise control filter. The nonminimum phase components of the secondary path exist in the frequency band below the lowest resonance frequency of the secondary loudspeaker. Based on this fact, we design a noise control filter by using band-limited white noise only with the low frequency components below the lowest resonance frequency in advance. Then, we design another adaptive noise control filter by using the band-limited white noise with high frequency components above the lowest resonance frequency. Finally, we combine these filters in the frequency domain. Through the computer simulations, we show the difficulty to handle the nonminimum phase components in the ANC system.

GPU implementation of a fast active noise control algorithm with multiple reference signals

Traditional active noise control (ANC) systems are mostly implemented on digital signal processor (DSP). Due to the inadequate computational power of the DSP, especially in applications with multiple reference signals, the DSP is unable to update the optimal control filter for different types of noise. Hence, Graphics Processing Unit (GPU) has been incorporated to the ANC system to enhance its computational power. In this work, a DSP-CPU-GPU computing architecture is adopted to improve the computational performance of the ANC system and ensure the real-time signal processing. In addition, a fast ANC algorithm on the GPU is employed to update the control filters to handle different reference signals. Finally, the effectiveness of the method is verified by experiments in the condition of multiple reference signals.

Improved direct-parallel active noise control systems for applications with narrowband noises

Rotary machinery generates noises at the fundamental frequency and its harmonics. The direct-parallel form active noise control (ANC) system, which is capable of reducing multiple narrowband noises, uses many harmonically related sinusoids as the reference input. The idea of direct-parallel form ANC is to split these sinusoids into several mutually exclusive sets, so each set has frequencies spaced out as far as possible. This paper proposes an improved direct-parallel form method to separate the reference sinusoidal signals and to enhance the noise reduction performance. Several experiments regarding to the ANC with a muffler model is made to verify the performance of the proposed method.

Time response of active sound control with a harmonic acoustic pneumatic source: simulations and experimental results

Active noise control is studied as a solution to reduce the blade passing frequency tonal noise of turbofans during landing and takeoff. A promising alternative to loudspeakers used as secondary sources is the Harmonic Acoustic Pneumatic Source (HAPS), that has been designed to generate a high harmonic noise level controllable in amplitude and phase using slow time varying signals. The objective is to design, characterize and optimize an active control system capable of following a time varying primary noise. A configuration with a loudspeaker acting as a primary source, a HAPS mounted laterally on a rectangular duct and an error microphone is considered. A first single-input-single-output controller for the case of plane wave control has been tested and allowed a convergence time of about 2 seconds to reach 20 dB attenuation of the acoustic pressure at 440 Hz. The results are consistent with simulations of the system and the convergence time can be explained by the dynamics of the HAPS. This study is a first step towards the objective of performing multimodal active noise control in duct with multiple sources in presence of flow.

Optimal selection of reference microphone for active noise control

This paper proposes two methods for selecting a reference microphone from multiple microphones, focusing on the correlation between the reference signal and the desired signal and the causality constraint of the signal, in order to effectively reduce noise arriving from various locations. In the first method, a threshold is set for the correlation between the reference signal and the desired signal, and a microphone that satisfies the causality constraint is selected as the reference microphone from microphones with correlation values that exceed this threshold. On the other hand, the second method selects a microphone with the highest correlation between the reference signal and the desired signal as the reference microphone among the microphones that satisfy the causality constraint. We demonstrate through simulation experiments that the active noise control system using these proposed methods can provide stable and effective noise reduction for noise arriving from various locations. It is also shown that both methods can reselect an appropriate reference microphone when the noise source moves.

Delayed-X harmonic synthesizer cancelling narrow bandpass noises by control signals via aural cartilage conduction

When a transducer is put on an aural cartilage, the transmitted vibration generates sound in the external auditory canal (i.e., cartilage conduction). A hearing device based on the cartilage conduction does not need occluding the external auditory canal. When an active noise control can adapt only to unwanted noise, the device enables natural conversations with unprocessed voice in the noisy environment (selective cancelation). To accomplish the selective cancelation, we proposed delayed-X harmonics synthesizer (DXHS) algorithm to minimize the damage for the speech quality. A target noise in this study was bandpass noise through a gammatone filter (center frequency: 500 Hz) overlapping the speech spectrum. After tracing the spectral envelope of the noise by using linear predictive coding (LPC), the DXHS outputted five pure tones distributed around the peak of envelope, and each step size parameter was adjusted according to the amplitude of the envelope. As results, our proposed method showed the noise reduction of 11.3 dB maintaining the speech quality in the computer simulations. During the adaptation, the step size adjustment enabled round off the spectral peak of the bandpass noise to avoid sharpening it.

A study of the ultrasonic and audible frequency response of commercial loudspeakers for use as parametric acoustic arrays

Parametric acoustic loudspeakers (PAL), also known as parametric acoustic arrays (PAA), are speakers that use ultrasonic waves to generate directive audible sound. They emit an ultrasonic carrier modulated in amplitude by the desired audible signal, and due to non-linear propagation in air, this signal is reproduced in the audible range. Typical applications include audio reproduction for entertainment, but also active noise control and acoustic measurement of material properties. PAA typically consist of an array of piezoelectric transducers set on a surface. However, there are other speakers in the market that, due to their characteristics, could also achieve the PAL effect. This work examines the performance of commercial speakers when reproducing. First, the ultrasonic frequency response of each speaker is examined in free-field conditions using exponential sine sweeps (ESS). This enables searching for potential carrier frequencies to modulate the ESS in the ultrasonic range. The ESS are next modulated in the desired ultrasonic region and emitted through each speaker, obtaining their audible and ultrasonic impulse responses. The results show that some commercial speakers can also operate as PALs, which is interesting from an industrial point of view as it lowers costs and simplifies the assembly process.

Global active noise control using SIMO near-field systems - Simulation and technical implementation

The technical implementation of a single-input multiple-output (SIMO) active near-field noise control (ANC) system designed for global low-frequency noise control is presented. The SIMO control strategy is motivated by noise control simulations based on a direct boundary element method (BEM) ansatz formulated in this paper. The suitability of the chosen BEM formulation and SIMO control strategy is accompanied and confirmed by extensive experiments and comparison to analytical calculations based on isotropic sources. The influence of parameters such as the positioning of the error microphone, the membrane velocity required for optimal global reduction, the effects of phase inaccuracies and the number of actuators on global reduction are investigated. The real-time control of the SIMO system is technically implemented on field programmable gate array (FPGA) hardware using a frequency domain block FxLMS algorithm. The iterative algorithm converges in less than 0.1 s for the examined frequency range from 100 Hz to 1000 Hz. Measurements using various circular SIMO array configurations showed reductions in sound power of up to 85\%, aligning closely with the numerical results.

Generalization of noise insulation afforded by common window designs with active noise control exposed to moving noise source

A window device that can provide noise insulation while maintaining natural ventilation is highly desirable and is especially sought after in heavily noise-polluted and hot-humid climates cities, such as Southeast Asian cities. However, a solution to provide such a window is non-trivial because the design principles guiding acoustics and ventilation are diametrically opposed. While louvre windows have traditionally been used in communal, healthcare, and some educational setting to provide a balance between acoustics and ventilation benefits, it is still sorely lacking to provide sufficient insertion loss without sacrificing ventilation entirely. A new plenum window design has recently garnered research and market interest to tackle the dichotomous problem. Additionally, the application of active noise control (ANC) in windows is gaining popularity and offers potential solutions to improve noise control without compromising ventilation. However, it remains unclear how different traditional and modern window designs compare in terms of their acoustic performance, especially when exposed to non-stationary noise sources such as urban traffic, a major noise pollutant. Thus, the present study seeks to provide a generalization of insertion loss provided by different window designs exposed to moving sources including a tangent study on ANC implementation via a time-domain approach.

Comparison of active and passive vibration control techniques for electric drive power electronic subsystem: Experimental validation

Reducing vibration and noise from power electronics components is vital for enhancing the performance and acceptance of electric vehicles, emphasizing the need for effective mitigation strategies in sustainable transportation. This paper compares passive and active vibration techniques, with a specific focus on utilizing particle damping for passive vibration control. The method achieves vibration reduction through viscoelastic deformation and friction resulting from the movement and collisions of granular material within the cavity. This contribution outlines diverse design strategies for integrating particle dampers into power electronic components. The active control approach, operating typically in the 50 Hz to 1200 Hz frequency range, can concurrently support passive noise treatments. Piezoelectric ceramics serve as both actuators and sensors in active noise reduction. Following the identification of dominant mode shapes, appropriate actuator and sensor positions are chosen. The control problem of the smart system is then addressed, opting for a velocity feedback control algorithm in a real collocated design. This algorithm computes input signals for actuators bonded to the outer surface, achieving significant active damping effects. Lab-tested techniques are validated in real-world conditions with a full-scale electric-drive toolkit, affirming their efficacy in reducing vibration and noise and underscoring their potential for implementation in electric vehicles.

Computation-efficient virtual sensing approach with multichannel adjoint least mean square algorithm

Multichannel active noise control (ANC) systems are designed to create a large zone of quietness (ZoQ) around the error microphones, however, the placement of these microphones often presents challenges due to physical limitations. Virtual sensing technique that effectively suppresses the noise far from the physical error microphones is one of the most promising solutions. Nevertheless, the conventional multichannel virtual sensing ANC (MVANC) system based on the multichannel filtered reference least mean square (MCFxLMS) algorithm often suffers from high computational complexity. This paper proposes a feedforward MVANC system that incorporates the multichannel adjoint least mean square (MCALMS) algorithm to overcome these limitations effectively. Computational analysis demonstrates the improvement of computational efficiency and numerical simulations exhibit comparable noise reduction performance at virtual locations compared to the conventional MCFxLMS algorithm. Additionally, the effects of varied tuning noises on system performance are also investigated, providing insightful findings on optimizing MVANC systems.

Expanding road noise cancellation to higher frequencies

Active vehicle Road Noise Cancellation (RNC) systems effectively reduce persistent vehicle rumble and booming noise which is very difficult to control with traditional NVH measures, particularly at low frequencies. Therefore, more and more vehicles are adapting RNC systems in their production applications. Most current RNC systems cancel low frequency structure-born noise, which is typically below 400 Hz. Although it provides appreciable noise attenuation, remaining high frequency noise contents still requires mitigation for a premium cabin experience. This study targets a next generation RNC system development which extends noise cancellation frequency range up to 1 kHz. High frequency RNC system (HF-RNC) development begins with analyzing limiting factors of the current RNC systems. Theoretical and practical limitations of the current system are discussed. Then, new technology and enablers to overcome those limitations are introduced. New enablers investigated herein in includes feedforward microphones, low latency system, headrest speakers and microphones, and head tracking system. HF-RNC system architecture is defined to comprise extended features and enablers. Low latency software is ported into a development platform which is based on a commercial DSP. The new HF-RNC system demonstrates noise cancellation up to 1 kHz when applied to an electric vehicle.