Active Noise Cancellation System Research Articles

Active Noise Cancellation Health Management Method

Ensuring the robustness of vehicle systems and features is a key aspect of customer satisfaction and therefore is of vital importance to Original Equipment Manufacturers (OEMs). Both initial quality and quality over the life of the vehicle are important aspects to customers. Therefore, some features and systems require an active approach at monitoring system health. The intent of Active Noise Cancellation (ANC) systems in vehicles is to increase the customer's perception of vehicle refinement and brand quality. Due to the nature of ANC system operation, it is critical that the system does not go divergent resulting in unwanted noise being heard by the customer. So, a method to monitor the ANC system operation and performance is required to ensure robustness. Despite tuning ANC systems considering expected vehicle build tolerances, vehicle aging and customer specific use cases, an ANC system can occasionally still go divergent in the field. An ANC audit procedure is included in the system software to verify functionality and performance at End of Line (EOL), repair centers or verified though an Over the Air (OTA) procedure. This type of procedure can verify the vehicle's acoustic cavity response and update ANC tuning parameters to account for any changes. This paper will show vehicle examples of why an ANC health monitoring system is needed and how we developed, implemented, and utilized an ANC audit procedure to improve ANC system robustness and customer satisfaction.

Active noise cancellation with FPGA - practical considerations

Active noise cancellation (ANC) has been successfully applied to mitigate noise in many applications, such as in headphones. Besides algorithm development and computer simulation, developing an ANC system involves many practical considerations. From hardware selection to fixed-point implementation, many practical constraints can prevent a good algorithm from functioning properly on the hardware. This paper discusses the development of an ANC prototype system using Field-Programmable Gate Array (FPGA) hardware. The paper also reviews several practical issues that were encountered in the development of the prototype, the symptom and root cause of each issue, and the solutions to mitigate them. The final ANC prototype system successfully cancels noise of both tonal and broadband contents.

A high-precision distributed neural processor for efficient computation of a new distributed FxSMAP-L algorithm applied to real-time active noise control systems

During the last decade, there has been growing interest in developing active noise cancellation (ANC) systems since they have emerged as a potential solution in the noise reduction of indoor or outdoor sources. Regarding the last point, if the users need to reduce the noise in some extended areas, a very-large amount of microphones and loudspeakers are required. As a consequence, the ANC system demands a large amount of computation. One potential solution can be given if the information is partitioned and distributed into several computing systems since the use of a centralized computing system could be insufficient. However, current distributed strategies demand a huge computationally cost. Therefore, the development of an efficient distributed ANC system to be applied in practical real-time ANC applications is a challenging task. Here, we present two contributions, which involve the development of a new variant of the filtered-x set membership affine projection-like algorithm to save a large amount of computational cost and the design of a FPGA-based distributed neural processor to efficiently simulate the proposed algorithm. Specifically, we improve two aspects to create a compact and high-performance distributed neural processor. The first aspect is linked to the improvement of the processing system. In particular, we make extraordinary efforts to optimize existing spiking neural arithmetic circuits, which are highly demanded in the computation of the proposed algorithm. The second improvement is related to the development of a new communication scheme based on cutting-edge variants of spiking neural P (SN P) systems to efficiently perform the data distribution between multiple FPGAs. To demonstrate the computational capabilities of the proposed FPGA-based distributed neural processor, we develop an acoustic sensor network as proof-of-concept. Our results have demonstrated that the proposed distributed FPGA-based neural processor can be used in practical real-time ANC applications.

EC-ANC: Edge Case-Enhanced Active Noise Cancellation for True Wireless Stereo Earbuds

In this paper, we propose an edge case-enhanced active noise cancellation (EC-ANC) system that integrates a piezo microphone, a signal processor, and a wireless module into the charging case of TWS earbuds. Considering the fact that sound travels much faster in solid materials than in the air, the piezo microphone on the edge case will pick up a lookahead signal before it reaches the earbuds. The lookahead signal is very useful for real-time noise cancellation, especially for eliminating high-frequency, unpredictable, and high dynamic range noises. Benefiting from the speed advantage of sound traveling in solid materials, EC-ANC performs well when the charging case is either close to the user or near the noise source. This allows EC-ANC to be easily applied to various noise cancellation scenarios. We implemented EC-ANC on Intel MAX 10 FPGA, and then validated its advantages over the popular ANC method adopted by Bose, Sony, and Apple. According to experiment results, EC-ANC can achieve higher noise attenuation in the 4 kHz range compared with Bose QuietComfort 20 (QC20) and Bose QuietComfort Earbuds (QCE). Even without the noise-absorbing material, EC-ANC’s performance at higher frequencies is comparable to QC20 and QCE.

Numerical modeling of an active noise reduction system in the engine exhaust pipe

Numerical simulations of the exhaust pipe of the internal combustion engine with an active noise cancellation system are being reported. It is proposed to introduce an additional controlled sound source opposite in phase to the sound waves coming from the engine into the engine exhaust pipe. A round plate that performs rotational vibrations with a given frequency and amplitude is assumed to be the sound source. The ideal gas model is taken as an equation of state. The realizable k-ε turbulence model is applied to simulate the compressible gas flow. Using a direct method based on changing the position of the damper at each time step, the additional sound source created by the damper was modeled. The damper motion was realized within the framework of the sliding mesh approach. A spherical mesh segment capable of rotating during calculations was created. The influence of the plate size and the incoming sound wave parameters on the operation of the active noise cancellation system of an internal combustion engine was evaluated. The dependences of the amplitude of oscillations of static and total pressure at the output of the noise reduction system on the amplitude and radius of the oscillating damper were obtained. The simulations were conducted for various values of the exhaust radius, and the effect of the size of the expansion chamber in front of the oscillating damper was studied. The obtained results indicate that the proposed active noise cancellation system is able to reduce the engine noise level by 10 dB. It is shown that an increase in the plate radius leads to an increase in the efficiency of the noise suppression system. However ,at the same time, the level of aerodynamic resistance that the noise suppression system provides to the gas flow also increases, which can lead to a decrease in engine power characteristics.

A Reduced Complexity Random Fourier Filter Based Nonlinear Multichannel Narrowband Active Noise Control System

Linear-in-the-parameters nonlinear controllers are widely used for active noise cancellation (ANC) in the presence of nonlinearities in the system. However, the performance of such controllers deteriorates significantly in highly nonlinear systems and also in the presence of nonlinear harmonic distortion. To overcome these issues, a kernel filtered-x least mean square (KFxLMS) algorithm based narrowband ANC system has been recently reported in the literature. We observe that the large memory size and high computational complexity of the KFxLMS algorithm hinder its implementation in real-time ANC systems. To alleviate these issues, a single channel random Fourier filter based FxLMS (RFFxLMS) algorithm is proposed in this brief. The above formulation is then extended to the multichannel scenario, and an RFF based multichannel narrowband ANC system is developed to achieve noise reduction over a broader area. The computational load of the proposed multichannel approach is further reduced by using a partial updating method. The simulation study shows that the overall performance of the proposed schemes is significantly better than the existing nonlinear methods.

Comparative study for Active Noise Cancellation using Adaptive filtering and Standing wave pattern

Noise pollution is one of the most fundamental challenges facing our environment, causes health problem, communication inefficiency and degrade the performance of works due to lack of concentration, thus, mitigating this impact becomes an unavoidable requirement of time to protect people's health and the environment. This noise may originate from several sources including industrial machinery, system parts wear out, and adjacent environmental acoustics. To mitigate this noise effect, an Active Noise Cancellation (ANC) headphone is achieved by two effective techniques; Adaptive filtering and Standing wave phenomenon. In this work, an ANC system is designed using both adaptive filtering and standing wave techniques, the former one basically utilizes single-channel feedforward whereas the latter one utilizes both single-channel feedforward and feedback control. LMS adaptive filter algorithm is the basic component of the designed ANC headphone. For simulation, a noise-free signal will be used as the desired audio signal and a gaussian distributed noise as the unwanted noise signal, these are combined to form noise corrupted speech signal. Propose algorithms performance were evaluated based on the ability to mitigate effects of different frequency broad-band noise signals and of different Noise to Signal ratio. Evaluation measures used are; convergence rate and noise reduction in dB. Result reveals ANC headphone using standing wave technique has better performance at mitigating noise frequency below 800Hz, with low SNR than Adaptive filtering. However, at higher frequencies above 1000Hz, ANC headphone using Adaptive filtering has good performance of masking high frequencies up to 22dB.

A New Method for Active Cancellation of Engine Order Noise in a Passenger Car

This paper presents a novel active noise cancellation (ANC) method to reduce the engine noise inside the cabin of a car. During the last three decades, many methods have been developed for the active control of a quasi-stationary narrowband sinusoidal signal. However, since the interior noise signal is non-stationary with a fast frequency variation when the car accelerates rapidly, these methods cannot stably reduce the interior noise. The proposed method can reduce the interior noise stably even if the speed of the car is changed quickly. The method uses an adaptive filter with an optimal weight vector for the active control of such an engine noise. The method of determining the optimal weight vector of an adaptive filter is demonstrated. In order to validate the advantages of the proposed method, a conventional method and the proposed method are simulated with three synthesized signals. Finally, the proposed method is applied to the cancellation of booming noise in a sport utility vehicle. We demonstrate that the performance of the ANC system with the proposed algorithm is excellent for the attenuation of engine noise inside the cabin of a car.

Accelerometer-Based Acoustic Control: Enabling Auscultation on a Black Hawk Helicopter

During aeromedical patient transport, acoustic noise levels in excess of 90 dB make auscultation with a stethoscope virtually impossible. Existing approaches to address this noise in literature have relied on the use of either passive shielding of the stethoscope sensing element or active noise cancellation (ANC) with the use of additional reference microphone sensors. These solutions have achieved inadequate performance. In this paper, custom instrumented stethoscopes are used to obtain structural vibration and acoustic data from a UH-60 Black Hawk helicopter. The data show that the structural vibrations contribute significantly more to stethoscope signals than air-borne acoustic noise. Therefore, a novel adaptive acoustic control system using a reference accelerometer is pursued. By varying the levels of acoustic and vibrational noise sources in a controlled laboratory environment, the benefits and limitations of microphone or accelerometer-based active noise control are investigated and compared. Experimentally simulating the field acoustic and vibration characteristics of the UH-60 Black Hawk helicopter, the accelerometer-based ANC system is shown to provide significantly superior performance. The accelerometer-based ANC system yields an average 25-dB reduction in ambient noise levels over the entire relevant frequency range, thereby enabling successful auscultation for the first time in this military aircraft environment.

Active Noise Cancellation using Online Wavelet Based Control System: Numerical and Experimental Study

Reaction wheels (RWs) used for attitude control of space vehicle systems usually encounter with undesired wide band noises. These noises which significantly affect the performance of regulator controller must tune the review or review rate of RWs. According to wide frequency band of noises in RWs the common approaches of noise cancellation cannot conveniently reduce the effects of the noise. Therefore, the advanced analyzer of frequency domain signal processing such as wavelets must be used to realize the noise cancellation. In this regards, only the online application of wavelets can be practical. In this paper, an online active noise canceller based on online wavelet theory is employed to omit the effects of undesired noise. In this way, dynamic identification of a RW as well as wavelet delay compensation are used simultaneously to design an active noise cancellation system. Numerical and experimental investigations of KNTU test setup as a hard ware in the loop system show the preferences of the proposed method of online noise cancellation.

Sound transmission acrosss a plenum window with an active noise cancellation system

A series of experiments was conducted in the present study in an attempt to understand how the implementation of active noise control would affect the sound transmission across a plenum window. A simple squared pressure control scheme with three error sensors equi-spaced on the vertical centerline of the indoor window opening was adopted. The secondary control loudspeakers were fixed close to the outdoor window opening. The effects of secondary control loudspeaker orientation relative to the plenum cavity and their locations on the performance of the active control were investigated. Results show that the active control system with two loudspeakers located symmetrically about the plenum cavity horizontal centerline facing directly the incoming noise gives the best performance. However, the effective frequency range is restricted to that below the first asymmetric mode cut-off frequency in the window gap direction. The active control performance is improved when the reverberation strength of the receiver chamber is reduced in general.

Evaluation of a Traffic Noise Predictive Model for an Active Noise Cancellation (ANC) System

PURPOSES : The purpose of this thesis is to evaluate the effectiveness of an active noise cancellation (ANC) system in reducing the traffic noise level against frequencies from the predictive model developed by previous research. The predictive model is based on ISO 9613-2 standards using the Noble close proximity (NCPX) method and the pass-by method. This means that the use of these standards is a powerful tool for analyzing the traffic noise level because of the strengths of these methods. Traffic noise analysis was performed based on digital signal processing (DSP) for detecting traffic noise with the pass-by method at the test site. METHODS : There are several analysis methods, which are generally divided into three different types, available to evaluate traffic noise predictive models. The first method uses the classification standard of 12 vehicle types. The second method is based on a standard of four vehicle types. The third method is founded on 5 types of vehicles, which are different from the types used by the second method. This means that the second method not only consolidates 12 vehicle types into only four types, but also that the results of the noise analysis of the total traffic volume are reflected in a comparison analysis of the three types of methods. The constant percent bandwidth (CPB) analysis was used to identify the properties of different frequencies in the frequency analysis. A-weighting was applied to the DSP and to the transformation process from analog to digital signal. The root mean squared error (RMSE) was applied to compare and evaluate the predictive model results of the three analysis methods. RESULTS : The result derived from the third method, based on the classification standard of 5 vehicle types, shows the smallest values of RMSE and max and min error. However, it does not have the reduction properties of a predictive model. To evaluate the predictive model of an ANC system, a reduction analysis of the total sound pressure level (TSPL), dB(A), was conducted. As a result, the analysis based on the third method has the smallest value of RMSE and max error. The effect of traffic noise reduction was the greatest value of the types of analysis in this research. CONCLUSIONS : From the results of the error analysis, the application method for categorizing vehicle types related to the 12-vehicle classification based on previous research is appropriate to the ANC system. However, the performance of a predictive model on an ANC system is up to a value of traffic noise reduction. By the same token, the most appropriate method that influences the maximum reduction effect is found in the third method of traffic analysis. This method has a value of traffic noise reduction of 31.28 dB(A). In conclusion, research for detecting the friction noise between a tire and the road surface for the 12 vehicle types needs to be conducted to authentically demonstrate an ANC system in the Republic of Korea.

Real-Time Detection of Unstable Control Loop Behavior in a Feedback Active Noise Cancellation System for In-Ear Headphones

Active noise controls are used in a wide field of applications to cancel out unwanted surrounding noise. Control systems based on the feedback structure however have the disadvantage that they may become unstable during run-time due to changes in the control path—in this context including the listener’s ear. Especially when applied to active noise cancellation (ANC) headphones, the risk of instability is associated with the risk of harmful influence on the listener’s ear, which is exposed to the speaker in striking distance. This paper discusses several methods to enable the analysis of a feedback ANC system during run-time to immediately detect instability. Finally, a solution is proposed, which identifies the open loop behavior parametrically by means of an adaptive filter to subsequently evaluate the coefficients regarding stability.

도로교통소음 저감을 위한 Active Noise Cancellation System 적용 및 평가

도로교통소음 저감을 위한 Active Noise Cancellation System 적용 및 평가

A perceptually motivated active noise cancellation system for hearing impaired listeners: An overview

Nowadays most hearing impaired (HI) patients are fitted with either open-fitting or vented-fitting hearing aids (HAs) to reduce the occlusion effect. In an environment where strong low-frequency ambient noise is present, significant noise energy can directly leak into the ear canal bypassing noise reduction algorithms in the HAs and may reduce speech intelligibility and listening comfort for HA users. One way to mitigate such an issue without occluding the ear canal is to implement an active noise cancellation (ANC) system inside the ear canal. Traditional ANC systems are designed to minimize the total sound pressure level in the ear canal. However, this may not necessarily lead to an optimal solution from the perceptual perspective (e.g., loudness may be reduced instead of being minimized as a result). In this paper, a perceptually motivated feedback ANC system is presented: a spectral shaping filter is applied to the residual error signal to minimize the loudness for HI listeners. In addition, implications of the practical constraints introduced by the HAs are discussed based on acoustic simulations and experimental results.

Secondary path variation in human listeners and its effect on an active noise cancellation system

Active noise cancellation (ANC) has been applied to cancel the penetrated ambient noise in the ear canal for hearing impaired listeners [Zhang et al. (2012)]. The performance of the proposed ANC system depends on the characteristics of the secondary path (SP). In this study, we developed an in-ear ANC system where the error microphone and the miniature loudspeaker were both placed in the ear canal. In such a case, the SP response depends on the error microphone response, the loudspeaker response, and how the microphone, the loudspeaker, and the ear canal are acoustically coupled. A robust method was proposed to measure the SP response of the proposed ANC system under various coupling conditions using human listeners. Variations of the measured SP responses were analyzed both within each individual and across different individuals. The effect of the SP variations on the performance of the proposed ANC system was evaluated. The implications for improving the proposed ANC system will be discussed.

A Decisive Filtering Selection Approach For Improved Performance Active Noise Cancellation System

In this work we present a filtering selection approach for efficient ANC system. Active noise cancellation (ANC) has wide application in next generation human machine interaction to automobile Heating Ventilating and Air Conditioning (HVAC) devices. We compare conventional adaptive filters algorithms LMS, NLMS, VSLMS, VSNLMS, VSLSMS for a predefined input sound file, where various algorithms run and result in standard output and better performance. The wiener filter based on least means squared (LMS) algorithm family is most sought after solution of ANC. This family includes LMS, NLMS, VSLMS, VSNLMS, VFXLMS, FX- sLMS and many more. Some of these are nonlinear algorithm, which provides better solution for nonlinear noisy environment. The components of the ANC systems like microphones and loudspeaker exhibit nonlinearities themselves. The nonlinear transfer function create worse situation. This is a task which is some sort of a prediction of suitable solution to the problems. The Radial Basis Function of Neural Networks (RBF NN) has been known to be suitable for nonlinear function approximation (1). The classical approach to RBF implementation is to fix the number of hidden neurons based on some property of the input data, and estimate the weights connecting the hidden and output neurons using linear least square method. So an efficient novel decisive approach for better performing ANC algorithms has been proposed. I. OVERVIEW Acoustic Noise Cancellation is a method for reducing undesired noise. It is achieved by introducing a canceling anti-noise wave through secondary sources. These secondary sources are interconnected through an electronic system using a specific signal processing algorithm for the particular cancellation scheme. Noise cancellation makes use of the notion of destructive interference. When two sinusoidal waves are superimposed, the resultant waveform depends on the frequency amplitude and relative phase of the two waves. If the original wave and the inverse of the original wave encounter at a junction at the same time, total cancellation occurs. The challenges are to identify the original signal and generate the inverse noise cancellation on inverse wave without delay in all directions where noises interact and superimpose. We meet in our everyday life. Echo phenomena are interesting and entertaining, but their presences in communication networks are undesirable and represent a serious problem. Echo is delayed and degraded version of original signal which travels back to its source after several reflections or because of some other reason. Nature of echo signal can be either acoustic or electrical, and in order to reduce its undesired effect we employ echo cancellers. Design of echo cancellers requires an application of adaptive filter theory. Echo cancellers must work within specific time limits so adaptive algorithms must provide fast convergence of filter parameters. Weve been applying echo cancellers successfully for many years, but we always tend to improve them and increase their efficiency. The wiener filter based least means squared (LMS) algorithm family is most sought after solution of ANC. This family includes LMS , Fx-LMS, VFx-LMS, FsLMS and many more . Then there are Kalman filter algorithms which are basically based on recursive least square algorithm. Some of these are nonlinear algorithm, which provides better solution for non linear noisy environment. The components of the ANC systems like microphones and loudspeaker exhibit nonlinearities themselves. The non linear transfer function of primary and secondary path may itself create worse situation. II. BACKGROUND LITERATURE REVIEW

Directional cancellation of acoustic noise for home window applications

This paper focuses on an active noise cancellation system for a home window using a transparent acoustic transducer. In a traditional active noise cancellation system, direct microphone measurements are used for reference and error signals. In the case of the window application, both external and internal sound would be picked up by such microphones. This leads to adverse effects on the performance of the active noise cancellation system and also to distortion of the internal sound. To address this problem, a wave separation technique is proposed to separate the internal and external components of sound. The wave separation algorithm is based on the use of two microphones and an algorithm that separates components based on their direction of travel. An active noise cancellation system is implemented using wave separation for both the error and reference signal measurements. The performance of the resulting ANC system is experimentally tested in a cabin equipped with a window and results are presented. Experimental results show that the new system is able to accurately preserve desired internal sound while cancelling uncorrelated external noise.

Invisible speakers in home windows for simultaneous auxiliary audio playback and active noise cancellation

The use of a transparent thin film speaker in a home window can provide both an invisible audio playback device and an active noise cancellation system. However, several key challenges need to be addressed for development of such a system. A traditional feedforward active noise cancellation system uses direct microphone measurements for both reference and error signals. Such a system can degrade both the audio playback and the noise cancellation performance. Hence a wave separation algorithm is used in this paper for separation of the audio playback component from the external noise component for the reference signal. Further, an online adaptive secondary transfer function estimation method is used for accurate removal of the audio component from the error signal. Two approaches are attempted for the secondary transfer function estimation – use of source audio signals and use of additive white noise. The developed algorithms are evaluated in a scaled cabin equipped with a window and a transparent thin film actuator. Experimental results show that the developed system can preserve the auxiliary audio sound while cancelling external noise effectively. The system based on the use of source audio signals for secondary path estimation is found to yield the largest cancellation of external noise while producing the least amplitude of control inputs that cancel desired audio signals.

Real-time active noise control of magnetic resonance imaging acoustic noise

Magnetic resonance imaging (MRI) is extensively used in clinical and medical researches because MRI is non-invasive and non-radiation. However, using the MRI cause the loud acoustic noise generated by gradient switching. The MRI noise is annoying patients. Therefore, active noise cancellation (ANC) is used to solve this problem in this article. In this article, the main work is to implement real-time system using DSP. The noise generated by each planar imaging (EPI), which is generally used in fMRI researches, is recorded from 3 Tesla MRI for testing ANC system. The EPI signal is regular and predictable, means the signal like a pattern, we using LMS algorithm to training the signal and learning predict the noise spectrum. After the calculated the noise, we output the reverse single to we home-built headset.