Method to extract target signals of a known type from raw data containing an unknown number of target signals, interference, and noise
First Claim
1. A method for extracting intermittent, randomly occurring transient target signals of known type from a raw data source signal containing an unknown number of the target signals in addition to interfering signals or intrinsic noise signals, the method comprising:
- a) obtaining the raw data source signal from a sensor for detecting the passage of particles or bubbles in a fluid flow, wherein a target signal is generated by the sensor when detecting a particle or bubble;
b) defining quantifiable signatures or characteristics that respectively and independently represent the target signals, the interfering signals or the intrinsic noise signals, wherein the signatures comprise a frequency range of the target signals and a kurtosis value range of wavelet coefficients of respective wavelet scales of interest that reflect a transient nature of the target signals;
c) applying a Time-Invariant Wavelet Transform (TIWT) to decompose the raw data source signal into distinct data sets in a form of wavelet coefficients of the respective wavelet scales;
d) processing said data sets to identify a first group of data sets which display the signatures or characteristics representing the interfering signals or intrinsic noise signals and a second group of data sets which display the signatures or characteristics representing the target signals;
e) setting the data sets of the first group to zero; and
f) applying an inverse transform to the processed data sets in order to reconstruct a processed output signal.
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Abstract
A signal analysis method extracts transient target signals of known type from a raw data source signal that contains an unknown number of target signals. The method can enhance the analysis of data obtained from in-line oil-debris sensors. The method comprises steps of: defining signatures of the known target signal, and of at least one of the intrinsic noise and interfering signals; performing a mathematical transform that decomposes the raw data into distinct data sets; using the signal signatures to identify and nullify the data sets containing noise and interfering signal signatures; using the target signal signatures to identify the data sets containing target signal components, or may further use a thresholding rule to remove intrinsic noise from said data sets, and finally applying the inverse transform to the processed data sets in order to reconstruct an enhanced output signal.
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Citations
15 Claims
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1. A method for extracting intermittent, randomly occurring transient target signals of known type from a raw data source signal containing an unknown number of the target signals in addition to interfering signals or intrinsic noise signals, the method comprising:
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a) obtaining the raw data source signal from a sensor for detecting the passage of particles or bubbles in a fluid flow, wherein a target signal is generated by the sensor when detecting a particle or bubble; b) defining quantifiable signatures or characteristics that respectively and independently represent the target signals, the interfering signals or the intrinsic noise signals, wherein the signatures comprise a frequency range of the target signals and a kurtosis value range of wavelet coefficients of respective wavelet scales of interest that reflect a transient nature of the target signals; c) applying a Time-Invariant Wavelet Transform (TIWT) to decompose the raw data source signal into distinct data sets in a form of wavelet coefficients of the respective wavelet scales; d) processing said data sets to identify a first group of data sets which display the signatures or characteristics representing the interfering signals or intrinsic noise signals and a second group of data sets which display the signatures or characteristics representing the target signals; e) setting the data sets of the first group to zero; and f) applying an inverse transform to the processed data sets in order to reconstruct a processed output signal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A method of enhancing the capability of a sensor for sensing a particle or bubble in a fluid flow, the sensor being adapted for generating transient target signals when particles or bubbles in the fluid pass through the sensor, the method comprising steps of:
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a) defining quantifiable signatures of the target signals, having a known frequency range of the target signals and a known kurtosis value range of wavelet coefficients of respective wavelet scales of interest that reflect a transient nature of the target signals; b) defining quantifiable signatures of interfering signals and intrinsic noise signals, having two known kurtosis value ranges of wavelet coefficients of each wavelet scale that correspond to the interfering signals and correspond to the intrinsic noise signals, respectively; c) obtaining a raw data sample signal in a time domain from the sensor in use for monitoring the fluid flow; d) applying a Time-Invariant Wavelet Transform (TIWT) to said raw data sample signal to effect a decomposition of said raw data sample signal into a plurality of data sets in a form of wavelet coefficients of respective wavelet scales; e) processing the data sets to calculate a kurtosis value for each data set to compare the kurtosis value for each data set with the kurtosis value range defined in step (a) or the kurtosis value ranges defined in step (b), in order to identify a first group of data sets which display the signatures representing the interfering signals and the intrinsic noise signals and a second group of data sets which display the signatures representing the target signals, and then setting the data sets of the first group to zero; f) applying a thresholding rule to process the data sets of the second group in order to reduce any intrinsic noise signals which remain in the data sets of the second group; and g) constructing a processed output signal by applying an inverse transform to the data sets processed in steps (e) and (f).
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Specification