Cyclic Wiener Filter Research Articles

A Two-Stage Method for Weak Feature Extraction of Rolling Bearing Combining Cyclic Wiener Filter with Improved Enhanced Envelope Spectrum

Due to the interference of various strong background signals, it is often difficult to extract effective features by using conventional methods such as envelope spectrum analysis when early weak fault arises in rolling bearing. Inspired by the current two main research directions of weak fault diagnosis of rolling bearing, that is, the enhancement of impulse features of faulty vibration signal through vibration analysis and the selection of fault information sensitive frequency band for further envelope spectrum analysis, and based on the second-order cyclostationary characteristic of the vibration signal of faulty bearing, a two-stage method for weak feature extraction of rolling bearing combining cyclic Wiener filter with improved enhanced envelope spectrum (IEES) is proposed in the paper. Firstly, the original vibration signal of the rolling bearing’s early weak fault is handled by cyclic Wiener filter exploiting the spectral coherence (SCoh) theory and the noise components are filtered out. Then, SCoh is applied on the filtered signal. Subsequently, an IEES method obtained by integrating over the selected fault information sensitive spectral frequency band of the SCoh spectral is used to extract the fault features. The innovation of the proposed method is to fully excavate the advantages of cyclic Wiener filter and IEES simultaneously. The feasibility of the proposed method is verified by simulation firstly, and vibration signals collected from accelerated bearing degradation tests and engineering machines are used to further verify its effectiveness. Additionally, its superiority over the other state-of-the-art methods is also compared.

Signal Enhancement of Helicopter Rotor Aerodynamic Noise Based on Cyclic Wiener Filtering

The research on helicopter rotor aerodynamic noise becomes imperative with the wide use of helicopters in civilian fields. In this study, a signal enhancement method based on cyclic Wiener filtering was proposed given the cyclostationarity of rotor aerodynamic noise. The noise was adaptively filtered out by performing a group of frequency shifts on the input signal. According to the characteristics of rotor aerodynamic noise, a detection function was constructed to realize the long-distance detection of helicopters. The flight data of the Robinson R44 helicopter was obtained through the field flight experiment and employed as the research object for analysis. The detection range of the Robinson R44 helicopter after cyclic Wiener filtering was increased from 4.114 km to 17.75 km, verifying the feasibility and effectiveness of the proposed method. The efficacy of the proposed detection method was demonstrated and compared in the far-field flight test measurements of the Robinson R44 helicopter.

Aerodynamic noise separation of helicopter main and tail rotors using a cascade filter with Vold-Kalman filter and cyclic Wiener filter

The noise issue has become an important factor limiting the massive application of helicopters as the requirements for helicopter reliability and comfort continue to increase. As the primary noise source of helicopters, the main and tail rotor aerodynamic noise should be separated for individual noise reduction investigations. According to the frequency domain characteristics, the rotor aerodynamic noise can be divided into tonal noise and broadband noise. A cascade filtering method with Vold-Kalman filter and cyclic Wiener filter is proposed in this paper to separate the tonal and modulated broadband noise of the main and tail rotors, respectively. The classical method only considers the periodic characteristics of the main and tail rotor aerodynamic noise for harmonic separation. The broadband noise is not considered within the separation of interest due to its randomness, which leads to the inaccuracy of the conventional method for the aerodynamic noise separation of the main and tail rotors. The broadband noise exhibits a second-order cyclostationarity due to the periodic modulation of the rotational motion of the rotor. According to its cyclostationarity, while considering the periodicity of tonal noise for harmonic separation, the proposed cascade filtering method also performs the separation of broadband noise. More precise separations of the main and tail rotor can be obtained by this method. The efficacy of the proposed cascade filtering method is demonstrated in both the simulation and wind tunnel noise measurement.

Research on the sharpness of combustion noise of three-cylinder GDI engine based on adaptive cyclic Wiener filter method

In order to analyze the sharpness of combustion noise of the gasoline direct injection (GDI) engine, the in-cylinder pressure and noise of different loads and speeds of a three-cylinder GDI engine are measured. An adaptive cycle Wiener filter method is proposed to separate the combustion noise. The result indicated that the proposed method can overcome the drawbacks of the original Wiener filter method and is able to separate high-frequency combustion noise components more accurately and effectively. The sharpness of the combustion noise is calculated by the Zwicker method and Aures method, and the comparison results show that the Aures method is more suitable for evaluating combustion noise. The influence of different loads and speeds on the sharpness of combustion noise is investigated by the proposed method systematically. The results indicated that at low speed (1500 r/min), the combustion noise and sharpness will increase with the load while at medium (3000 r/min) and high (5500 r/min) speeds, the combustion noise under half load (50%) has the highest sharpness. Excessive high load (100%) and too low load (0%) both suppress the generation of combustion noise. As for the same engine load, a higher engine speed will lead to higher combustion noise and sharpness.

The Acoustic Imaging of the Broadband Dipole Sound Sources of Helicopter Rotor in the Wind Tunnel Test

Acoustic wind tunnel test is an important way to study the noise mechanism of helicopter rotors. The broadband dipole noise distribution of helicopter rotors can be obtained from the acoustic wind tunnel measurement, which can be extremely helpful in analyzing the pulsation noise mechanism of rotor blade surfaces. However, during acoustic imaging of broadband dipole sources, there is often a problem of unwanted noise interference from other experimental setups of the wind tunnel, such as the rotor shaft. To accurately visualize the broadband dipole sound sources, in this paper, a moving dipole-type sources beamforming method suitable for the wind tunnel environment is proposed. The reduced-rank cyclic Wiener filter is firstly developed to extract the rotor broadband noise signal in wind tunnel tests; a beamforming method for moving dipole sound sources is then proposed according to the characteristics of the generation and propagation of the dipole sound sources. The BO105 helicopter rotor model is tested in the FL-17 aeroacoustic wind tunnel of the China Aerodynamics Research and Development Center (CADRC). The wind tunnel test results demonstrate that the method can effectively suppress noise interference in the wind tunnel and accurately extract and visualize broadband dipole sources of rotor blade surfaces.

Cyclostationary Crosstalk Cancelation in High-Speed Transmission Lines

The theoretical and experimental evaluation of the cyclostationary random data transferring process corrupted by the individually and jointly cyclostationary crosstalk interference is presented. The interference and the message signals were measured by the real time digital oscilloscope. Autocorrelation functions were evaluated by synchronous cyclic averaging procedure. The analyzed periodic two-dimensional impulse response of the time-varying filter allows to obtain the output random process with the same cyclic frequency at the output of the filter by separation of orthogonal stationary waveforms constituting the input cyclostationary random process (CSRP). The filtering of the measured random process was implemented by the cyclic Wiener filter. The evaluation of the two-dimensional autocorrelation function and eye diagrams at the output of the cyclic Wiener filter showed significant reduction of the independent interference components in the estimated message signal.

Optimal filtering of angle-time cyclostationary signals: Application to vibrations recorded under nonstationary regimes

Mechanical signals are often a mixture of multiple components produced by different sources. The separation of these components is beneficial for differential diagnosis, fault severity assessment and prognosis. An optimal way to accomplish this task is to apply a linear periodically time-variant filter, also known as the cyclic Wiener filter (CWF), assuming the signal to be cyclostationary and assuming that the source periodicity is a priori known. For the first assumption to be valid, the machine must operate under a stationary regime which is generally a restrictive condition. This paper addresses this issue by proposing a formal extension of the CWF to the nonstationary regime case within the angle-time cyclostationary framework. This framework was specifically designed to describe and process machine signals recorded under variable speed conditions. In addition to the theoretical formalisation of the so-called angle-time CWF, a simple and fast algorithm based on the Welch estimator is proposed. The efficiency of the new filter is demonstrated, and compared to the classical one, on synthetic and real vibration signals.

The Relationship Between the Cyclic Wiener Filter and Fractionally Spaced Equalizers

This paper presents a different interpretation of the cyclic Wiener filter (CWF) for digital (in-phase/quadrature) IQ-modulated signals, such as phase-shift keying (PSK) or quadrature amplitude modulations (QAM). We demonstrate that the CWF can be implemented as a multirate filter instead of the frequency-shift (FRESH) filter implementation found in the literature. The multirate implementation consists of a fractionally spaced equalizer (FSE) followed by a pulse shaping filter, thus establishing a direct relationship between the CWF and FSEs. Afterwards, the results from the study are applied to develop a simple blind adaptive algorithms for signal estimation, which are benchmarked against the most common CWF implementation based on FRESH filters.

Reconstruction of cyclostationary sound source based on a back-propagating cyclic wiener filter

The reconstruction of sound sources is recognized as a typical inverse problem consisting of back-propagating the measurements of an array onto the sources plane based on the propagation function of the sound. In this paper, the reconstruction of the cyclostationary sources in noisy environment is investigated. The cyclostationary sources assumption covers a wide range of sound sources with a cyclic transfer of energy in time, which are usually generated from the repetitive physical mechanism of a rotating machine. The rotating machines are commonly assembled with the mechanical components generating the stationary sources. The proposed back-propagating cyclic wiener filter aims at reconstructing only the cyclostationary sources from the total measurements of with stationary noises. The proposed method can be considered as an extension of the classic cyclic wiener filter, where the latter can only filter the mixed signals in the time domain whereas the former can reconstruct the spatial sources by integrating the propagation function. Thus, it extended the classic cyclic Wiener filter from the filtration of measurements to the reconstruction of sources by a cascade of the cyclic wiener filter and the Bayesian focusing. The proposed method is first validated by a laboratory experiment in a semi-anechoic chamber. Next, an industrial application involving engine bay on-site measurements is investigated to validate the proposed method: a cyclostationary source on the High Pressure Pump (HPP) is reconstructed, free of the noise interference from the engine.

Extraction and imaging of aerodynamically generated sound field of rotor blades in the wind tunnel test

Abstract The acoustic beamforming has been widely applied in the imaging of flow-induced aeroacoustic sound sources. However, the measured signals of the rotor blades often accompanied with the unwanted interference from other components of the experimental setup in the wind tunnel test (for example, the rotor shaft and the stand), which results in the undistinguished sources in the beamforming result. In this paper, the signals of rotor blades are defined first as the cyclostationary process based on the Ffowcs Williams-Hawkings (FW-H) equation in the form of Wold-Cramer decomposition, which connects the statistical definition of rotor blades signals with the wave propagation model of moving sources. Then the developed cyclostationary signal processing tools of a second order, specifically the reduced-rank cyclic Wiener filter, can be applied in the wind tunnel test of rotor blades. The rotor blades signals can be extracted from the noisy measurements with other interferences, which aide to purify the image results of beamforming in the final experiment of wind tunnel test.

Feature extraction of rolling element bearing’ compound faults based on cyclic wiener filter with constructed reference signals

Feature extraction of rolling element bearing’s compound faults is a challenging task due to the complexity and the mutual coupling phenomenon among the kinds of faults. A new method based on cyclic wiener filter with constructed reference signals is proposed in the paper. The reference signals of the rolling element bearing’ inner race fault, outer race fault and rolling element fault are created respectively based on the rolling element bearing’ theoretical fault frequencies. Here, the created signals are used as the expected responses. Then the observed compound faults signal and the constructed reference signal are input into the cyclic wiener filter together. At last, the envelope demodulation method is applied on the filtered signals respectively and satisfactory fault feature extraction results are obtained. The effectiveness of the proposed method is verified through simulation. Furthermore, the advantages of the proposed method over other signal handling method such as spectral kurtosis (SK) are verified through experiment.

Cyclic Wiener Filtering Algorithm in Discrete Cosine Transform Domain for Vibration Signal

In order to solve the problem that the effect of using cyclic Wiener filter directly to remove the noise on the non-stationary vibration signal is poor, the paper applies discrete cosine transform to the cyclic Wiener filter, proposing the cyclic Wiener filtering algorithm in discrete cosine transform domain for the vibration signal. Using the energy concentration characteristic of discrete cosine transform and the linear phase characteristic of cyclic Wiener filtering, the paper adopts the method of combining both of them with segmented processing to give full play to the performance of the Wiener filter and achieves a better filtering effect with a lower filter order. Combining with industrial field turbine vibration signal, paper makes a simulation analysis for this algorithm. The result of simulation shows that the algorithm has a good noise filtering effect, and the filtered signal has no obvious phase distortion. So, the algorithm is suitable for removing noise on vibration signal and the filtering effect is better than just using cyclic Wiener filter or DCT filter only.

Weak fault feature extraction of rolling bearing based on cyclic Wiener filter and envelope spectrum

In vibration analysis, weak fault feature extraction under strong background noise is of great importance. A method based on cyclic Wiener filter and envelope spectrum analysis is proposed. Cyclic Wiener filter exploits the spectral coherence theory induced by the second-order cyclostationary signal. The original signal is duplicated and shifted in the frequency domain by amounts corresponding to the cyclic frequencies. The noise component is optimally filtered by a filter-bank. The filtered signal is analyzed by performing envelope spectrum. In the envelope spectrum, characteristic frequencies are quite clear. Then the most impactive part is effectively extracted for further fault diagnosis. The effectiveness of the method is demonstrated on both simulated signal and actual data from rolling bearing accelerated life test.

Nonparametric Interference Suppression Using Cyclic Wiener Filtering: Pulse Shape Design and Performance Evaluation

In the future, there will be a growing need for more flexible but efficient utilization of radio resources. Increased flexibility in radio transmission, however, yields a higher likelihood of interference owing to limited coordination among users. In this paper, we address the problem of flexible spectrum sharing where a wideband single carrier modulated signal is spectrally overlapped by unknown narrowband interference (NBI) and where a cyclic Wiener filter is utilized for nonparametric NBI suppression at the receiver. The pulse shape design for the wideband signal is investigated to improve the NBI suppression capability of cyclic Wiener filtering. Specifically, two pulse shaping schemes, which outperform existing raised cosine pulse shaping schemes even for the same amount of excess bandwidth, are proposed. Based on computer simulation, the interference suppression capability of cyclic Wiener filtering is evaluated for both the proposed and existing pulse shaping schemes under several interference conditions and over both AWGN and Rayleigh fading channels.

Causal Wiener filter banks for periodically correlated time series

A causal filter bank implementation of the cyclic Wiener filter for periodically correlated (PC) time series is developed. By converting a PC time series into a vector-valued wide-sense stationary (WSS) time series, the existing literature on factorization of spectral density matrices may be utilized. However, because PC analytic and equivalent baseband signals are generally complex improper, spectral factorization algorithms must be adapted to the improper case. Based on the factorization of the spectral density matrix for the equivalent WSS vector process, causal synthesis and whitening filters for PC time series can be built. These techniques are exploited to implement a causal cyclic Wiener filter as a multirate filter bank or an equivalent polyphase structure. This filter bank is shown to be an efficient equivalent implementation of a frequency shift (FRESH) filter. Therefore, the results derived in this paper also show how to build a causal FRESH cyclic Wiener filter.

Separation of combustion noise and piston-slap in diesel engine—Part I: Separation of combustion noise and piston-slap in diesel engine by cyclic Wiener filtering

The main purpose of this study is to characterize the relative noise given out by a diesel engine, around the Top Dead Centre (TDC) by quantifying the proportions of “mechanical noise” originating mainly from piston-slap on the one hand and ‘thermal noise” originating from combustion on the other hand. Two different approaches are described here to solve this problem. In the first part of the paper, the cylinder pressure is measured and used as a reference in order to reconstruct the thermal noise. Next, we propose a method based on applying a cyclic Wiener filter to the measured cylinder pressure in order to separate the noises of mechanical and thermal origins. The final result is to reduce the engine resulting noise. The second part of the paper is devoted to blind source separation (BSS) methods applied on signals issued from accelerometers placed on one of the cylinders. It develops a BSS method based on a convolutive model of non-stationary mixtures and introduces a new method based on the joint diagonalization of time varying spectral matrices of the observations. Both methods are then applied to real data and the estimated sources are finally validated by several physical arguments.

Linear suppression of wideband data-like interference in DS/SS communications

In this paper, a linear receiver is proposed and its performance is analyzed for direct-sequence spread-spectrum communications with wideband data-like interference. Two groups of communicators employing generalized random spreading are considered, and the signals are assumed to have harmonically related cyclostationarity periods. First, the output signal-to-interference ratio (SIR) of a general correlation receiver is derived in the frequency domain, and the key system parameters that affect the structure of the interference are identified. Then, a linear interference suppression scheme based on the maximum SIR (MSIR) criterion is proposed, and a receiver structure similar to the cyclic Wiener filter is derived. Numerical results show that the proposed linear MSIR receiver significantly outperforms the conventional correlation receiver by effectively suppressing the wideband data-like interference.

Blind Multiuser Detection for Long-Code CDMA Systems with Transmission-Induced Cyclostationarity

We consider blind channel identification and signal separation in long-code CDMA systems. First, by modeling the received signals as cyclostationary processes with modulation-induced cyclostationarity, long-code CDMA system is characterized using a time-invariant system model. Secondly, based on the time-invariant model, multistep linear prediction method is used to reduce the intersymbol interference introduced by multipath propagation, and channel estimation then follows by utilizing the nonconstant modulus precoding technique with or without the matrix-pencil approach. The channel estimation algorithm without the matrix-pencil approach relies on the Fourier transform, and requires additional constraint on the code sequences other than being nonconstant modulus. It is found that by introducing a random linear transform, the matrix-pencil approach can remove (with probability one) the extra constraint on the code sequences. Thirdly, after channel estimation, equalization is carried out using a cyclic Wiener filter. Finally, since chip-level equalization is performed, the proposed approach can readily be extended to multirate cases, either with multicode or variable spreading factor. Simulation results show that compared with the approach using the Fourier transform, the matrix-pencil-based approach can significantly improve the accuracy of channel estimation, therefore the overall system performance.