US 11,635,345 B2Granted

System for separating periodic frequency of interest peaks from non-periodic peaks in machine vibration data

AssigneeComputational Systems, Inc.

InventorStewart V. Bowers, III

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Abstract

A statistical method is used to separate periodic from non-periodic vibration peaks in machine vibration spectra. Generally, a machine vibration spectrum is not normally distributed because the amplitudes of periodic peaks are significantly large and random relative to the generally Gaussian noise. In a normally distributed signal, the statistical parameter Kurtosis has a value of 3. The method sequentially removes each largest amplitude peak from the peaks in a frequency region of interest in the spectrum until the Kurtosis has a value of three or less. The removed peaks, which are all considered to be periodic, are placed into a candidate peak list. As the process of building the candidate peak list proceeds, if the kurtosis of the remaining peaks in the frequency region of interest falls to three or less, the process stops and the candidate peak list is defined.

Claims20

Dependent claims

An apparatus for acquiring and analyzing periodic information in vibration associated with a machine, the apparatus comprising:

a vibration sensor attached to the machine that generates a vibration signal;
a data collector in communication with the vibration sensor that receives and conditions the vibration signal, the data collector including an analog-to-digital converter for converting the vibration signal to digital vibration data;
and
a processor that receives the digital vibration data and executes operational instructions for processing the digital vibration data to:
(a) generate a vibration waveform based on the digital vibration data;
(b) perform a Fast Fourier Transform on the vibration waveform to generate a vibration spectrum that includes vibration amplitude peaks;
(c) determine a frequency of interest based at least in part on a rotational speed of a component of the machine;
(d) determine a frequency region of interest within the vibration spectrum in relation to the frequency of interest;
(e) compile a located peak list of the vibration amplitude peaks at frequencies falling within the frequency region of interest;
(f) arrange the vibration amplitude peaks in the located peak list in order of descending amplitude or ascending amplitude to generate a sorted peak list in which a largest amplitude peak is first and a smallest amplitude peak is last, or in which the smallest amplitude peak is first and the largest amplitude peak is last;
(g) calculate a kurtosis value based on amplitudes of all peaks in the sorted peak list;
(h) if the kurtosis value is greater than a kurtosis threshold, remove the peak having the largest amplitude from the sorted peak list and place it in a largest peak list;
(i) repeat steps (g) and (h) until the kurtosis value is less than or equal to the kurtosis threshold;
and
(j) selecting one or more frequency of interest candidates, which are one or more frequencies of peaks in the largest peak list that fall within a delta frequency range around the frequency of interest.

12 more elements

A computer-implemented method for analyzing periodic information in digital vibration data collected for machine performance analysis, the method comprising:

(a) generating a vibration waveform based on the digital vibration data;
(b) performing a Fast Fourier Transform on the vibration waveform to generate a vibration spectrum that includes vibration amplitude peaks;
(c) determining a frequency of interest based at least in part on a rotational speed of a component of a machine;
(d) determining a frequency region of interest within the vibration spectrum in relation to the frequency of interest;
(e) compiling a located peak list of the vibration amplitude peaks at frequencies falling within the frequency region of interest;
(f) arranging the vibration amplitude peaks in the located peak list in order of descending amplitude or ascending amplitude to create a sorted peak list in which a largest amplitude peak is first and a smallest amplitude peak is last, or in which the smallest amplitude peak is first and the largest amplitude peak is last;
(g) calculating a kurtosis value based on amplitudes of all peaks in the sorted peak list;
(h) if the kurtosis value is greater than a kurtosis threshold, removing the peak having the largest amplitude from the sorted peak list and place it in a largest peak list;
(i) repeating steps (g) and (h) until the kurtosis value is less than or equal to the kurtosis threshold;
and
(j) selecting one or more frequency of interest candidates, which are one or more frequencies of peaks in the largest peak list that fall within a delta frequency range around the frequency of interest.

8 more elements

A computer-implemented method for analyzing periodic information in digital vibration data to determine a rotational speed of a shaft in a machine, the method comprising:

(a) generating a vibration waveform based on the digital vibration data;
(b) performing a Fast Fourier Transform on the vibration waveform to generate a vibration spectrum that includes vibration amplitude peaks;
(c) determining a gear mesh frequency of interest based at least in part on a rotational speed of a gear of a machine, wherein the gear has a number of gear teeth;
(d) determining a frequency region of interest within the vibration spectrum in relation to the gear mesh frequency of interest;
(e) compiling a located peak list of the vibration amplitude peaks at frequencies falling within the frequency region of interest;
(f) arranging the vibration amplitude peaks in the located peak list in order of descending amplitude or ascending amplitude to create a sorted peak list in which a largest amplitude peak is first and a smallest amplitude peak is last, or in which the smallest amplitude peak is first and the largest amplitude peak is last;
(g) calculating a kurtosis value based on amplitudes of all peaks in the sorted peak list;
(h) if the kurtosis value is greater than a kurtosis threshold, removing the peak having the largest amplitude from the sorted peak list and place it in a largest peak list;
(i) repeating steps (g) and (h) until the kurtosis value is less than or equal to the kurtosis threshold;
(j) selecting one or more gear mesh frequency candidates, which are one or more frequencies of peaks in the largest peak list that fall within a delta frequency range around the gear mesh frequency of interest, wherein the delta frequency range is bounded by an upper frequency limit and a lower frequency limit, wherein:
the upper frequency limit equals the number of gear teeth on the shaft associated with the gear mesh frequency of interest times a synchronous speed of the machine, and
the lower frequency limit equals the number of gear teeth on the shaft associated with the gear mesh frequency of interest times 120% of a full load speed of the machine;
and
(k) determining the rotational speed of the shaft based on dividing the one or more selected gear mesh frequency candidates by the number of gear teeth on the shaft associated with the gear mesh frequency of interest.

11 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/227,271Filed 10 Apr 2021 · continuation in part
Priority: 2 Jul 2013
Published: US 2021/0231528 A129 Jul 2021
Granted: 25 Apr 2023
Term ends: Not estimatedThe source records don’t support an estimate.

Classification8 codes

G01M 13/028
Gearings; Transmission mechanisms: acoustic or vibration analysis
G01M 13/045
Bearings: acoustic or vibration analysis
G01H 1/00
Measuring characteristics of vibrations in solids by using direct conduction to the
G01H 3/06
Frequency: by electric means

Family

Application61/842,035Us provisional application · filed 2 Jul 2013
Application14/316,883Parent of this continuation-in-part · filed 27 Jun 2014
Application62/410,935Us provisional application · filed 21 Oct 2016
Application15/697,911Parent of this continuation-in-part · filed 7 Sep 2017
Application62/813,863Us provisional application · filed 5 Mar 2019
Application16/515,793Parent of this continuation-in-part · filed 18 Jul 2019
US 10,416,126 B2Parent of this continuation-in-part · filed 17 Sep 2019
US 2021/0231528 A1Pre-grant publication · published 29 Jul 2021
US 11,002,641 B2Parent of this continuation-in-part
US 9,791,422 B2Parent of this continuation-in-part
US 2015/0012247 A1Published application
US 2018/0011065 A1Published application
US 2019/0346343 A1Published application
US 11,635,345 B2This patent

From the US filing history. Foreign family members aren’t listed.