FXLMS Algorithm Research Articles

Active Vibration Control Performance Comparison Based on Middle Pedestal Stiffness Using a Mobility Model and the Narrowband Fx-LMS Technique

Vibrations generated from equipment mounted on ships radiate into the water and affect covert operation capabilities. Accordingly, various studies are being conducted to reduce vibration transmitted from mounted equipment. In this study, a system consisting of mounting equipment, a 3-axis active mount, a middle pedestal, and a lower mount of the middle pedestal was modeled using a finite element analysis program, and a mobility model was constructed by calculating the frequency response function between the positions required for analysis. The error signal (primary path) obtained using the mobility model and the response at the operating point by the control force of the actuator (secondary path) are applied to the narrowband Fx-LMS algorithm for vibration control, and the control performance was compared. Through coupling analysis of the middle pedestal, the control influence according to the rigidity of the middle pedestal was analyzed. As a result of the control simulation, the time required for vibration control was controlled approximately 6 times faster in the model, with increased stiffness of the middle pedestal, and the vibration reduction performance was predicted to improve by a minimum of 0.9 dB and a maximum of 13.3 dB. Through this study, a simulation model that can provide a guide for the design of the middle pedestal of a ship was obtained, and it is expected that it can be utilized for a preliminary design review before manufacturing the middle pedestal of a ship.

New Multi-Channel VSMFxLMS Algorithm for Vibration Reduction of Gear Systems

At present, the active control of gear vibration mostly relies on existing algorithms. In order to achieve effective vibration reduction of the gear system, particularly during the vibration process, this paper proposes a multi-channel VSMFxLMS algorithm based on the FxLMS algorithm. This novel approach takes into account the time-varying nature of the vibration signal during gear vibration. Adaptive filter power coefficients are updated in a skip-tongue variable-step manner using momentum factors. Firstly, the paper establishes the dynamics model of the gear system and analyzes the nonlinear dynamic characteristics of the system. It then examines the vibration damping effect of the FxLMS algorithm and analyzes its performance under different gear system motion states, considering different step lengths and momentum factors. Lastly, the proposed VSMFxLMS algorithm is compared with the FxLMS algorithm, highlighting the superiority of the former. Overall, this research highlights the potential of a multi-channel VSMFxLMS algorithm in reducing vibrations in gear systems. The study optimizes the performance of gear systems while using advanced control strategies.

Analysis and control of hydrofoil vortex-induced vibration

This paper primarily investigates the relationship between the wake vortices and vortex-induced vibrations in hydrofoil structures, as well as explores effective methods to suppress structural vibrations in hydrofoils using a piezoelectric control system. By combining CFD simulations with PIV experiments, the study compared the vortex characteristics at the trailing edge of hydrofoils with different geometries. Furthermore, by integrating the results from the water tank experiments, the research revealed the sensitivity of vortex-induced resonance to the regularity and periodicity of the von Kármán vortex street. Subsequently, the FxLMS algorithm was fine-tuned based on a phenomenological model of vortex-induced resonance. Active control experiments on vortex-induced vibrations of the hydrofoil were conducted using a piezoelectric control system built on this algorithm, achieving a maximum vibration reduction rate of 56%. Finally, the instability and limitations of the control effectiveness were analyzed, and future research directions were proposed to improve control strategies and the system's temporal responsiveness.

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.

A reservoir computing approach in active noise control for vehicle applications

Reservoir Computing (RC) is an alternative approach to Recurrent Neural Networks (RNN) that can avoid some shortcomings of conventional gradient decent-training that are mainly related to high computational complexity and the reduced ability to "learn" long-range dependencies. In RC the input data are transformed into patterns in a high-dimensional space by an RNN called the "reservoir", which remains unchanged during training. The desired output signal is generated as a linear combination of the neuron's signals from the input-excited reservoir. The linear part of the RC architecture, which is called the "readout" can be trained with a simple learning algorithm such as linear regression. In this work an RC architecture is proposed for the attenuation of acoustic disturbances encountered in vehicle cabins such as aircrafts and yachts. At first, a dataset of acoustic pressure measurements from real-world cabins was used to generate the readout and reservoir layers. Subsequent computer simulations demonstrated that the proposed architecture can successfully attenuate such acoustic disturbances. Finally, the performance of RC in Active Noise Cancellation task was compared with both the linear FxLMS algorithm and a conventional RNN, showing that it has several advantages regarding acoustic pressure reduction combined with relatively low computational complexity.

Improved Active Noise Cancellation Using Variable Step-Size Combined Fx-LMS Algorithm

Improved Active Noise Cancellation Using Variable Step-Size Combined Fx-LMS Algorithm

Investigation of noise characteristics of electric vibrator utilizing acoustic camera and transfer path analysis

Abstract Mechanical equipment operation frequently results in noise generation, which can raise concerns regarding quality and safety. This study focuses on electric vibrators, essential electromechanical systems, with the goal of identifying the source and transfer path of noise. To achieve this objective, an acoustic camera positioning analysis was performed to approximate the distribution and characteristics of the noise. Building upon this foundation, a thorough evaluation of the transfer path and noise contribution was conducted. Subsequently, targeted noise suppression methods were implemented based on the properties of the noise. Primary noise sources were observed to be classified into wind turbulence and mechanical vibration based on operating conditions. Time-frequency analysis revealed the presence of low-frequency signals (around 50 Hz) and intermediate-frequency signals (around the resonant frequency), corresponding to wind-induced and mechanical response noise, respectively. Leveraging the characteristics of the noise and its transfer path, passive methods (Sound-absorbing rubber and Soundproof cotton) and active method (FxLMS algorithm) were employed. The findings of this study contribute to a better understanding of noise mechanisms and provide insights for noise emission strategies.

Piezoelectric-based smart structures for aero-engine blade: Piezoelectric layout optimization and vibration suppression tests

To promote the use of piezoelectric smart structures in aero-engine blades, this paper introduces a novel method for optimizing the layout of piezoelectric elements on the blade's surface and an active vibration control method, along with vibration suppression tests. A preprocessing method is introduced for the point cloud data of in-service blades to reconstruct the blade surface. An improved parameter-adaptive differential evolution algorithm is proposed to optimize the layout of piezoelectric actuators and sensors and accurately identify the hysteresis nonlinear model of piezoelectric elements. A Hammerstein model is constructed by cascading an asymmetric Bouc-Wen model with an ARX model to describe the rate-dependent hysteresis nonlinear characteristics of piezoelectric elements. An improved variable step-size FxLMS algorithm is proposed to balance the relationship between convergence speed and steady-state error in the control algorithm. The proposed layout optimization and vibration control algorithm are validated experimentally on an experimental platform under various disturbances, with results showing improved performance of the proposed VSS-FxLMS algorithm in terms of convergence and efficiency.

Multi-channel decentralized decoupling FxLMS algorithm and active vibration control experiment

When vibrations generated by marine machinery propagate through a ship’s hull into the ocean, they produce low-frequency radiated noise with distinct “acoustic fingerprint” characteristics. This noise, characterized by stable and concentrated energy, long transmission distances, and difficulty in elimination, becomes the primary target for enemy sonar detection. Active vibration isolation serves as a critical method for reducing low-frequency vibrations in ships and enhancing their acoustic stealth performance. However, control challenges persist, including multi-frequency excitation, frequency fluctuation, multi-channel coupling, and slow convergence speed. To address these issues, this paper introduced an innovative multi-channel decentralized decoupling filtered-x least mean square (DMFxLMS) algorithm. Firstly, a recursive least squares identification algorithm with a forgetting factor was proposed, taking into account the characteristics of single-input, multi-output and multi-input, and multi-output control systems, effectively enhancing the algorithm’s convergence speed and control accuracy. Secondly, based on the decentralized decoupling control concept, the multi-channel control system was simplified into parallel single-channel control loops. The control weight coefficient updates were only related to adjacent error signals, significantly reducing the algorithm’s computational complexity. Thirdly, an anti-impact link was designed to improve the algorithm’s robustness, considering the interference caused by other mechanical equipment during the control process. The influence of abnormal error signals in the control weight coefficient correction term was suppressed, and a percentage function was introduced to limit the output signal. Finally, the feasibility and effectiveness of the DMFxLMS algorithm were verified through simulations and experiments. The results demonstrated that the DMFxLMS algorithm achieved significant control effects for both constant frequency line spectrum excitation and frequency fluctuating line spectrum excitation, fulfilling the objective of reducing base vibration. The DMFxLMS algorithm exhibited fast convergence and excellent robustness, making it suitable for practical engineering applications.

Application of an improved wide–narrow-band hybrid ANC algorithm in a large commercial vehicle cabine

In recent years, active noise reduction technology has become a research hotspot. However, most active noise reduction technologies are developed based on passenger vehicles and are not implemented in large commercial vehicles. The large commercial vehicle sound field space is large, the traditional active noise reduction method is difficult to implement. In order to explore this problem, this paper proposes an improved active noise control method for commercial vehicles: (1) based on the traditional notch filter, a notch FxLMS algorithm based on speed smoothing is proposed; (2) on the basis of the traditional wire–narrowband hybrid ANC algorithm, the reference signal weighting technology is introduced into the wide-band subsystem, and the notch FxLMS algorithm based on speed smoothing is used as the narrowband subsystem, so as to propose an improved wire-narrowband hybrid ANC algorithm. With the help of MATLAB, the simulation model of the designed algorithm is established, and the collected commercial vehicle test noise data is used as the reference signal to simulate and verify the proposed algorithm. The results show that the proposed method has certain practicability.

Pulse Train Fx-LMS Algorithm for Drive File Identification

A novel time-domain algorithm is proposed in this paper for the iterative estimation of drive files. A drive file is a synchronized batch of dynamic time series commands that are simultaneously sent to one or more actuators in a test rig that is designed for service environment replication (SER). When drive file commands are input to an SER test rig, the response of the article under test is similar to what was measured in a service environment. The proposed Pulse Train Filtered-X Least Mean Square (PT-Fx-LMS) algorithm is based on methods developed for active noise and vibration control (ANVC). A time-domain PT-Fx-LMS algorithm is shown through several simulation studies to rapidly converge to a dynamic solution in a small number of iterations for a one degree-of-freedom nonlinear suspension. The PT-Fx-LMS algorithm is also shown to enable targeted iteration over isolated time slices within the data set, which challenges conventional frequency-domain techniques.

Four-Channel Active Noise Control Modeling and Offline Simulation for Electric Bus Sound Quality Based on Two FxLMS Algorithms

Four-Channel Active Noise Control Modeling and Offline Simulation for Electric Bus Sound Quality Based on Two FxLMS Algorithms

Frequency-domain weighted FxLMS algorithm for feedback active noise control

Frequency-domain weighted FxLMS algorithm for feedback active noise control

Development of a Systematic Methodology for Active Noise Control with Vehicle Engine Mounts Excitation

Active noise control (ANC) technology using speakers as actuators has an excellent performance, but since it generates anti-noise signals in a path completely different from the vehicle's noise source, performance can be greatly reduced at a location far from the error sensor, and this problem can get worse as the frequency to be controlled increases. Another approach is the vibration-based ANC technology that excites the body member around the engine mount and reduces acoustic error signals in a passenger compartment. This approach has the advantage of being effective even at a distance from the error sensor and reducing vibration and noise together when trying to cancel out the structure borne noise generated by the engine because the paths from the primary source and the secondary source to the interior are almost identical. This paper presents a systematic methodology for this vibration-based ANC technology to achieve high performance in vehicles. First, through noise reduction simulation, the number of error sensors, the location of actuators, the force requirements, and an appropriate system are proposed. Next, to improve performance even with a small number of actuators and limited power when applying this technology in vehicles, an algorithm using the control effort weighting parameter is introduced into the existing FxLMS algorithm and modelled on the controller. Finally, a noise reduction control test is performed in a vehicle under static and driving conditions, and the results are reviewed.

An adaptive feed-forward active vibration isolation algorithm for input disturbance unbalanced MIMO systems

Multi-axis active vibration isolation systems often encounter order-of-magnitude differences in the perturbations in each input direction. This causes adaptive feedforward control systems to converge at a relatively slow rate, or possibly even diverge. To solve this problem, we propose an improved adaptive feedforward vibration isolation technique based on the classical FxLMS algorithm. Our approach constructs a weighted transformation matrix based on singular value decomposition, attenuates the uneven influence of the input perturbations, and effectively avoids the problems of slow convergence and poor stability faced by existing adaptive algorithms. This paper first describes the parameter update algorithm and the structure of adaptive feedforward algorithms. The convergence of the proposed algorithm is then analyzed, and the method for constructing the weighting matrix is introduced. Finally, the feasibility of the algorithm is verified using a multi-axis vibration isolation system simulation model. The simulation results show that the power spectrum of acceleration in the frequency domain from 0.1 to 100 Hz is attenuated by up to 70 dB under the condition of no excitation in a specific direction, demonstrating the vibration isolation effect of the algorithm. The relative deviation between the predicted and actual parameter error is no more than 6 %, which shows that the algorithm achieves good convergence. The proposed algorithm has potential applications in the active vibration isolation of space telescopes and high-precision optical equipment.

An augmented diffusion algorithm with bidirectional communication for a distributed active noise control system.

Recent studies on diffusion adaptation for distributed active noise control (DANC) systems have attracted significant research interest due to their balance between computational burden and stability compared to conventional centralized and decentralized adaptation schemes. The conventional multitask diffusion FxLMS algorithm assumes that the converged solutions of all control filters are consistent to each other, which is unrealistic in practice hence results in inferior performance in noise reduction. An augmented diffusion FxLMS algorithm has been proposed to overcome this problem, which adopts a neighborhood-wide adaptation and node-based combination approach to mitigate the bias in the converged solution of the multitask diffusion algorithms. However, the improvement comes at the expense of a higher computational burden and communication cost. All existing DANC systems, including the multitask and augmented diffusion algorithms, assume one-way communication between nodes. By contrast, this paper proposes a bidirectional communication scheme for the augmented diffusion algorithm to further reduce the memory requirement, computational burden, and communication cost. Simulation results in the free field and with measured room impulse responses both demonstrate that the proposed augmented diffusion algorithm with bidirectional communication can achieve a faster convergence speed than that based on one-way communication with a lower memory, computation, and communication burden.

An Efficient Narrowband FxLMS Algorithm for A 3-Axis Active Mount

The Active Mount (AM) controls the vibrations caused by the movement of a mechanical system resting on top of it. Vibration caused by mechanical systems often consists of several dominant frequency components. Therefore, we need an adaptive algorithm controlling tonal vibration components effectively. The FxLMS algorithm widely used for active vibration control raises several issues as the tone number and control channel increase. This paper proposes an efficient narrowband FxLMS algorithm for controlling multiple tonal vibrations occurring in a 3-axis AM. To this end, the secondary path's magnitude and phase responses are modeled tone-by-tone, independently using two-tap filters. Narrowband control filters are constructed for each tone using a narrowband signal model. In addition, a reference sensor is mounted on top of AM, from which tonal references are estimated using adaptive notch filters (ANFs). The proposed algorithm was simulated using transfer functions obtained in a 3-axis AM. Results show that the proposed algorithm effectively controls multiple tonal components by minimizing total errors measured along the 3-axis.

Investigation of Effect of Mean Flow on Active Noise Control System in Duct

The increasing demand for a quieter living environment has driven the development of noise reduction and control technologies. Previous research has demonstrated the significant impact of mean flow on the performance of noise reduction devices. While efforts have been made to enhance passive noise control systems in the presence of mean flow, research on the influence of mean flow on active noise control (ANC) systems is limited, particularly in terms of computational modeling. This study addresses this gap by investigating the effect of mean flow on ANC system performance using a validated virtual controller within a computational framework, complemented by experimental investigations. The acoustic propagation inside the computational domain is computed using the Computational Aeroacoustics method, and the ANC system is modeled using FxLMS algorithm with the virtual-controller method as proposed in our earlier work. Through experiments, it reveals that the presence of mean flow in duct reduces the performance of the ANC system. The numerical investigation exhibited a consistent trend in line with the experimental findings, showing a strong agreement between the 3D numerical simulations and experimental data. These numerical results offer compelling evidence that the computational framework used in this study accurately models the impact of mean flow on ANC systems.

An intelligent momentum perturbed variable step-size adaptive algorithm for fast converging HNANC systems

The existing methodologies for hybrid narrow-band active noise control (HNANC) systems utilises variants of the FXLMS algorithm, which typically resulted in degraded convergence and steady-state performance. In this paper, a class of variable step size (VSS) adaptive algorithms are explicitly developed for a HNANC system analyses and the convergence as well as the steady-state performance of the proposed framework are evaluated in comparison to the existing state-of-the-art. For an HNANC system designed to operate in a multiple noise environment, the VSS filtered-x LMS (VSSFXLMS) and momentum VSS filtered- x weight accumulated least mean square (MVSS-FXWALMS) algorithms are proposed. The proposed algorithm employs a variable step size that is inspired by the variable momentum factor, and combines these two parameters to drive the FXWALMS algorithm for an HNANC system in order to accomplish maximum noise reduction. In a multiple noise environment setup for an HNANC system, the proposed algorithm surpasses the state-of-the-art in nearly all conventional operating conditions. A detailed performance analysis of the proposed algorithm has been carried out using mean noise reduction ratio, steady-state power spectra at different conditions. The results demonstrate a significant improvement in noise reduction performance compared to the counterparts.

Double Panel Structure for Active Control of Noise Transmission

Passive noise reduction means are commonly used to reduce noise in the industry but, unfortunately, their effectiveness is poor in the low frequency range. By applying active structural acoustic control to the enclosure walls significant improvement of the insulating properties in this frequency range can be achieved. In this paper a model of double panel structure with ASAC is presented. The structure consists of two aluminium plates separated by an air gap. Two inertial magnetoelectric actuators and two piezoceramic MFC sensors were used for controlling the structure. A multichannel FxLMS algorithm with virtual error microphone technique is used as a control algorithm. The signal of a virtual error microphone is extrapolated basing on signals from MFC sensors. Performance of this actively controlled structure for tonal signals at selected frequencies is presented in the article. During the study, a double panel structure was mounted on one wall of sound insulating enclosure located in an acoustic chamber. During the measurements local and global reduction of noise test signal was investigated.