AM FM Research Articles

Sparse signal decomposition method based on multi-scale chirplet and its application to the fault diagnosis of gearboxes

Based on the chirplet path pursuit and the sparse signal decomposition method, a new sparse signal decomposition method based on multi-scale chirplet is proposed and applied to the decomposition of vibration signals from gearboxes in fault diagnosis. An over-complete dictionary with multi-scale chirplets as its atoms is constructed using the method. Because of the multi-scale character, this method is superior to the traditional sparse signal decomposition method wherein only a single scale is adopted, and is more applicable to the decomposition of non-stationary signals with multi-components whose frequencies are time-varying. When there are faults in a gearbox, the vibration signals collected are usually AM–FM signals with multiple components whose frequencies vary with the rotational speed of the shaft. The meshing frequency and modulating frequency, which vary with time, can be derived by the proposed method and can be used in gearbox fault diagnosis under time-varying shaft-rotation speed conditions, where the traditional signal processing methods are always blocked. Both simulations and experiments validate the effectiveness of the proposed method.

Visualization and enrichment of live putative cancer stem cell populations following p53 inactivation or Bax deletion using non-toxic fluorescent dyes

Putative cancer stem cell (CSC) populations efflux dyes such as Hoecsht 33342 giving rise to side-populations (SP) that can be analyzed or isolated by flow cytometry. However, Hoecsht 33342 is highly toxic, more so to non-SP cells, and thus presents difficulties in interpreting in vivo studies where non-SP cells appear less tumorigenic than SP cells in immunodeficient mice. We searched for non- toxic dyes to circumvent this problem as well as to image these putative CSCs. We found that the fluorescent dye calcein, a product of intracellular Calcein AM cleavage, is effluxed by a small subpopulation, calcein low population (CloP). This population overlaps with SP and demonstrated long term cell viability, lack of cell stress, and proliferation in several cancer cell lines when stained whereas Hoecsht 33342 staining caused substantial apoptosis and ablated proliferation. We also found that the effluxed dye D-luciferin exhibits strong UV-fluorescence that can be imaged at cellular resolution and spatially overlaps with Calcein AM. In order to evaluate the hypothesis that p53 loss promotes enrichment of putative CSC populations we used Calcein AM, D-luciferin, and Mitotracker Red FM as a counterstain to visualize dye-effluxing cells. Using fluorescence microscopy and flow cytometry we observed increased dye-effluxing populations in DLD-1 colon tumor cells with mutant p53 versus wild-type (WT) p53-expressing HCT116 cells. Deletion of the wild-type p53 or pro-apoptotic Bax genes induced the putative CSC populations in the HCT116 background to significant levels. Restoration of WT p53 in HCT116 p53-/- cells by an adenovirus vector eliminated the putative CSC populations whereas a control adenovirus vector, Ad-LacZ, maintained the putative CSC population. Our results suggest it is possible to image and quantitatively analyze putative CSC populations within the tumor microenvironment and that loss of pro-apoptotic and tumor suppressing genes such as Bax or p53 enrich such tumor-prone populations.

The envelope order spectrum based on generalized demodulation time–frequency analysis and its application to gear fault diagnosis

The generalized demodulation time–frequency analysis is a novel signal processing method, which is particularly suitable for the processing of multi-component amplitude-modulated and frequency-modulated (AM–FM) signals as it can decompose a multi-component signal into a set of single-component signals whose instantaneous frequencies own physical meaning. While fault occurs in gear, the vibration signals measured from gearbox would exactly display AM–FM characteristics. Therefore, targeting the modulation feature of gear vibration signal in run-ups and run-downs, a fault diagnosis method in which generalized demodulation time–frequency analysis and envelope order spectrum technique are combined is put forward and applied to the transient analysis of gear vibration signal. Firstly the multi-component vibration signal of gear is decomposed into some mono-component signals using the generalized demodulation time–frequency analysis approach; secondly the envelope analysis is performed to each single-component signal; thirdly each envelope signal is re-sampled in angle domain; finally the spectrum analysis is applied to each re-sampled signal and the corresponding envelope order spectrum can be obtained. Furthermore, the gear working condition can be identified according to the envelope order spectrum. The analysis results from the simulation and experimental signals show that the proposed algorithm was effective in gear fault diagnosis.

AM–FM techniques in the analysis of optical coherence tomography signals

The subtle tissue changes associated with the early stages of malignancies, such as cancer, are not clearly discernible even at the current, improved, resolution of optical coherence tomography (OCT) systems. However, these changes directly affect the spectral content of the OCT image that contains information regarding these unresolvable features. Spectral analysis of OCT signals has recently been shown to provide additional information, resulting in improved contrast, directly related to scatterer size changes. Amplitude modulation-frequency modulation (AM-FM) analysis, a fast and accurate technique for the estimation of the instantaneous frequency, phase, and amplitude of a signal, can also be applied to OCT images to extract scatterer-size information. The proposed technique could make available an extremely valuable tool for the investigation of disease characteristics that now remain below the resolution of OCT and could significantly improve the technology's diagnostic capabilities.

Time-varying frequency-shifting signal-assisted empirical mode decomposition method for AM–FM signals

A time-varying frequency-shifting signal-assisted empirical mode decomposition (EMD) method is presented in this paper. For AM–FM signals, if the extrema density (average number of extrema per unit length) is higher, the frequency is higher approximately, and vice versa. The assisted signal in this method is directly derived from the local extrema using the least square method, and avoids the difficulty that masking signals are not adaptively examined so that the masking signal may not always enable the EMD to generate true mono-component intrinsic mode functions (IMFs). Therefore, the constructed assisted signal is adaptive and suitable for the analysis of frequency-varying components. Compared with the traditional EMD, the method mainly solves the following problems of the traditional EMD: the traditional EMD fails to separate the modes whose frequencies are time-varying and lie within an octave, and fails to remove the time-varying frequency mode-mixing. The results of three experiments are given to show our method's performance and efficiency.

Application of the improved generalized demodulation time–frequency analysis method to multi-component signal decomposition

The generalized demodulation time–frequency analysis approach is a novel signal processing method, which is suitable for processing non-stationary signals, especially for processing amplitude-modulated and frequency-modulated (AM–FM) signals. The novelty of this method is that the signal whose time–frequency distributions are curved paths can be transformed into that whose time–frequency distributions are linear paths paralleling time axis by using generalized demodulation. Furthermore, the generalized demodulated signal can be decomposed into a number of mono-component signals whose instantaneous frequencies have physical meaning through the use of the maximal overlap discrete wavelet packet transform (MODWPT). Therefore, the complete time–frequency distributions of the original signal can be obtained. However, the generalized demodulation time–frequency analysis method fails to provide the time domain waveform of each mono-component signal. In this paper, aiming at the multi-component AM–FM signal, each mono-component signal of which only has single-sided spectra, the improvement to the generalized demodulation time–frequency analysis approach has been made and the improved method is introduced into certain multi-component AM–FM signal decomposition. The analysis results demonstrate that the validity of the proposed approach. In addition, the estimation of the phase function that is key step in the generalized demodulation time–frequency analysis approach is also discussed.

DC cancellation in the single-bit domain using ternary filtering

A structure for single-bit DC blocking is presented. This type of DC blocker is useful in practice to improve the stability and dynamic range of single-bit systems. The DC blocker is essentially a ternary filtering structure whose input and output are both assumed to be sigma–delta modulated bitstreams. Two techniques have been utilised to design the ternary filter to allow for implementation and performance comparison. Performance is tested for different kinds of single-bit format input signals, including sinusoidal, FM and AM–FM signals. The proposed DC blocker contains no multipliers and can easily be implemented with FPGA technology.

Research on iterated Hilbert transform and its application in mechanical fault diagnosis

Multicomponent AM–FM demodulation is an available method for machinery fault vibration signal analysis, so a new method for mechanical fault diagnosis based on iterated Hilbert transform (IHT) is proposed. The principle of computing the asymptotically exact multicomponent sinusoidal model for an arbitrary signal by iterating Hilbert transform is introduced, and some properties of IHT are analyzed. Theoretical analysis for the generic two-component signal shows that there are limitations in the direct estimation of instantaneous frequencies via the phase signals of the previously obtained model. Therefore, a smoothed instantaneous frequency estimation (SIFE) method based on difference operator and zero-phase digital low-pass filtering is proposed, and then the accuracy and validity of this method have been proved by the simulation results. The analysis results of the mechanical fault signals show that the weak features of these signals can be efficiently extracted with the proposed approach.

Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis

Targeting the advantages of Hilbert–Huang transform (HHT) and the characteristics of gear fault vibration signals, HHT is introduced into gear fault diagnosis. The concept of local Hilbert energy spectrum is proposed and two gear fault diagnosis approaches, namely, frequency family separation method based on EMD (empirical mode decomposition) and local Hilbert energy spectrum method, are put forward, which are applied to gear fault diagnosis. Considering that the gear fault vibration signal is a multi-component amplitude-demodulated and frequency-demodulated (AM–FM) signal and EMD could exactly decompose the AM–FM signal into a number of intrinsic mode functions (IMFs), each of which can be amplitude-demodulated or frequency-demodulated component, the frequency families could be separated effectively from the gear vibration signal by applying EMD to the gear vibration signal. Furthermore, when faults occur in gear, the energy of the gear vibration signal would change correspondingly, whilst the local Hilbert energy spectrum can exactly provide the energy distribution of the signal in certain frequency with the change of the time and frequency. Thus, the fault information of the gear vibration signal can be extracted effectively from the local Hilbert energy spectrum. The analysis results from the experimental signals show that both frequency family separation method based on EMD and local Hilbert energy spectrum method could extract the characteristics information of the gear fault vibration signal effectively.

Multicomponent AM–FM Representations: An Asymptotically Exact Approach

This paper presents, on the basis of a rigorous mathematical formulation, a multicomponent sinusoidal model that allows an asymptotically exact reconstruction of nonstationary speech signals, regardless of their duration and without any limitation in the modeling of voiced, unvoiced, and transitional segments. The proposed approach is based on the application of the Hilbert transform to obtain an amplitude signal from which an AM component is extracted by filtering, so that the residue can then be iteratively processed in the same way. This technique permits a multicomponent AM-FM model to be derived in which the number of components (iterations) may be arbitrarily chosen. Additionally, the instantaneous frequencies of these components can be calculated with a given accuracy by segmentation of the phase signals. The validity of the proposed approach has been proven by some applications to both synthetic signals and natural speech. Several comparisons show how this approach almost always has a higher performance than that obtained by current best practices, and does not need the complex filter optimizations required by other techniques

Adaptive modulated wavelet subband image coding

High quality, embedded, variable rate image compression can be achieved by decomposing an image into subbands of different sizes, modeling with one significant AM–FM component as well as encoding with a distinct procedure for each subband. In this paper, an adaptive subband decomposition using the modulated wavelet packet transform is proposed, where the adaptation of modulating frequencies is based on the energy spectral density in a resolution-recursive framework; and, each subband can be well represented by the modulated wavelets. An extension of SPIHT algorithm that is needed for encoding the complex-valued modulated wavelet coefficients is also presented. Experimental results show that the modulated wavelet subband image coding is preferable to both the wavelet coding and the JPEG standard.

Mobile multimedia antenna systems for station wagons and the achievable diversity effectiveness obtained by analysis of virtual test drives

For modern cars, antennas are required for AM reception, FM and TV diversity reception, weatherband reception (USA), terrestrial digital radio, remote control functions, keyless entry, mobile phone for all worldwide used systems, GPS, and in the future, satellite broadcast radio services. Those services cover the frequency range from 150 kHz up to 2.4 GHz. Such kind of a multiantenna system developed for station wagons is presented in this paper. The obtainable FM and TV diversity effectiveness is discussed for several types of antenna arrangements in detail. This value is the number of fictitious completely decorrelated antenna signals and is obtained by virtual test drives. The characteristic of the respective antennas under test is introduced in the software as antenna pattern, measured or calculated with respect to amplitude and phase. During the computer analysis the car with the antennas is driven virtually through a Rayleigh field scenario with desired and undesired signals.

Analysis of the ?dispersive? transmission of chirped digital optical signals

In optical transmission systems, the propagation of high-speed digital optical signals is affected by the joint action of AM–FM conversion due to the nonlinear chirping effect in a semiconductor laser and the chromatic dispersion of the optical fiber. The optical signal becomes not only attenuated, but even changed in shape in such a way that the system performance can be severely constrained. In this paper, the effect of the “dispersive” propagation of chirped digital signals in optical fiber is evaluated by an analytical model, which overcomes the asymptotic approaches of previous models and, unlike simulative approaches, permits us to maintain the sensitivity to the physical parameters governing propagation and to follow the evolution of the propagating optical pulse. ©2000 John Wiley & Sons, Inc. Microwave Opt Technol Lett 24: 287–290, 2000.

Time-varying coherent AM–FM demodulation and denoising of acoustic signals

Noise removal via linear time-invariant (LTI) filtering is most effective when the signal and noise spectra have minimal overlap in frequency. In particular, it can be difficult to extract, via LTI filtering, broadband signals from broadband noise, because often their spectra overlap. However, many broadband signals are locally narrow band (e.g., AM–FM signals with large FM and moderate to small AM), and this characteristic can be exploited to improve noise suppression for such signals. We present a method for extracting locally narrow band signals from broadband noise, based on an AM–FM decomposition of the signal and time-varying filtering. The center frequency and passband of a linear time-varying filter are determined from estimates of the instantaneous frequency and instantaneous bandwidth of the signal. Results on both synthetic signals and recorded whale sounds in ambient noise demonstrate a significant improvement in SNR compared to LTI-based filtering. [Supported by ONR Grant N00014-98-1-0680.]

Speech analysis and synthesis using an AM–FM modulation model

In this paper, the AM–FM modulation model is applied to speech analysis, synthesis and coding. The AM–FM model represents the speech signal as the sum of formant resonance signals each of which contains amplitude and frequency modulation. Multiband filtering and demodulation using the energy separation algorithm are the basic tools used for speech analysis. First, multiband demodulation analysis (MDA) is applied to the problem of fundamental frequency estimation using the average instantaneous frequency as estimates of pitch harmonics. The MDA pitch tracking algorithm is shown to produce smooth and accurate fundamental frequency contours. Next, the AM–FM modulation vocoder is introduced, which represents speech as the sum of resonance signals. A time-varying filterbank is used to extract the formant bands and then the energy separation algorithm is used to demodulate the resonance signals into the amplitude envelope and instantaneous frequency signals. Efficient modeling and coding (at 4.8–9.6 kbits/sec) algorithms are proposed for the amplitude envelope and instantaneous frequency of speech resonances. Finally, the perceptual importance of modulations in speech resonances is investigated and it is shown that amplitude modulation patterns are both speaker and phone dependent.

Theory of combined AM and high-harmonic FM mode locked laser

Closed form solutions for a simultaneously AM and high-harmonic FM mode locked laser system is presented. Analytical expressions for the pulsewidth and pulsewidth-bandwidth products are derived in terms of the system parameters. The analysis predicts production of 17 ps duration pulses in a Nd:YAG laser mode locked with AM and FM modulators driven at 80 MHz and 1.76 GHz for 1 W modulator input power. The predicted values of the pulsewidth-bandwidth product lie between the values corresponding to the pure AM and FM mode locking values.

Harmonic analysis and restoration of separation methods for periodic signal mixtures: Algebraic separation versus comb filtering

The problem of separating a mixture of periodic signals into its constituent components occurs in sound detection, biomedical signal processing, and in communications. Existing approaches to solving it are either based on harmonic selection in the frequency domain or on linear comb filtering in the time-domain. In this paper, the recently proposed matrix algebraic separation approach is analyzed in the frequency domain. The insight obtained via this analysis leads to the development of harmonic restoration techniques that fill in the information missing at the harmonics shared by the components and also to the development of constraints on the carrier frequencies and bandwidths for narrowband, bandpass, and periodic AM–FM components for minimum information loss. The restored methods are then applied to mixtures of sines and AM–FM signals. Differences between this improved approach and a similar improvement of the comb filtering approach are also emphasized.

Comparison between optical SCM systems using semiconductor laser diode or intensity external modulator at the transmitter

A comparison is presented concerning the use of a semiconductor laser or intensity external modulator at the transmitter of hybrid AM/QAM subcarrier multiplexed optical transmission systems. In the first case, several effects are considered, which give rise to different distortion phenomena: intrinsic “dynamic” distortions due to the interaction of photons and electrons in a semiconductor laser, clipping impulsive noise, an AM–FM conversion effect due to the joint action of semiconductor laser chirping fiber chromatic dispersion, and nonlinear distortions due to the Kerr effect. In the case of an external intensity modulator, the distortion noise due to its intrinsic nonlinear response is analyzed. The analysis provides useful information about the design and the performance evaluation of SCM-based optical access networks. © 1998 John Wiley & Sons, Inc. Microwave Opt Technol Lett 18: 23–27, 1998.

Instantaneous frequency and the conditional mean frequency of a signal

Time-varying frequency is a natural occurrence, the mathematical and physical description of which has been evolving for many decades. One description of time-varying frequency is the instantaneous frequency proposed by Gabor, defined as the derivative of the phase of the (analytic) signal. The interpretation of this quantity has been a subject of much investigation. One interpretation arising from time—frequency distribution theory is that instantaneous frequency is the average frequency at each time in the signal. We explore this interpretation in detail, and derive conditions on an arbitrary two-component AM—FM complex signal for which this interpretation is plausible. The situations for which these conditions are met are limited. We also show that while one can force the interpretation by generating a new complex representation (not necessarily analytic) for which the derivative of the phase coincides with the average frequency at each time and for which the real part of this complex signal is the given signal, the amplitude of this complex signal is generally unbounded. Thus, if instantaneous frequency is to interpreted as the average frequency at each time, the instantaneous amplitude must generally be unbounded. Conversely, if we insist that the instantaneous amplitude be bounded, then the instantaneous frequency generally cannot be interpreted as the average frequency at each time.

Instantaneous frequency and the conditional mean frequency of a signal

Abstract Time-varying frequency is a natural occurrence, the mathematical and physical description of which has been evolving for many decades. One description of time-varying frequency is the instantaneous frequency proposed by Gabor, defined as the derivative of the phase of the (analytic) signal. The interpretation of this quantity has been a subject of much investigation. One interpretation arising from time—frequency distribution theory is that instantaneous frequency is the average frequency at each time in the signal. We explore this interpretation in detail, and derive conditions on an arbitrary two-component AM—FM complex signal for which this interpretation is plausible. The situations for which these conditions are met are limited. We also show that while one can force the interpretation by generating a new complex representation (not necessarily analytic) for which the derivative of the phase coincides with the average frequency at each time and for which the real part of this complex signal is the given signal, the amplitude of this complex signal is generally unbounded. Thus, if instantaneous frequency is to interpreted as the average frequency at each time, the instantaneous amplitude must generally be unbounded. Conversely, if we insist that the instantaneous amplitude be bounded, then the instantaneous frequency generally cannot be interpreted as the average frequency at each time.