Machine fault prediction based on analysis of periodic information in a signal
A “periodic signal parameter” (PSP) indicates periodic patterns in an autocorrelated vibration waveform and potential faults in a monitored machine. The PSP is calculated based on statistical measures derived from an autocorrelation waveform and characteristics of an associated vibration waveform. The PSP provides an indication of periodicity and a generalization of potential fault, whereas characteristics of the associated waveform indicate severity. A “periodic information plot” (PIP) is derived from a vibration signal processed using two analysis techniques to produce two X-Y graphs of the signal data that share a common X-axis. The PIP is created by correlating the Y-values on the two graphs based on the corresponding X-value. The amplitudes of Y-values in the PIP is derived from the two source graphs by multiplication, taking a ratio, averaging, or keeping the maximum value.
1. An apparatus for acquiring and analyzing periodic information in vibration associated with a machine, the apparatus comprising:
a vibration sensor securely attached to the machine in a location providing a solid transmission path from a source of vibration within the machine to the vibration sensor, the vibration sensor for generating a vibration signal;
a data collector in communication with the vibration sensor, the data collector configured to receive and condition the vibration signal, the data collector comprising:
an analog-to-digital converter for converting the vibration signal to digital vibration data; and
memory for buffering the digital vibration data; and
a periodic information processor operable to receive the digital vibration data, the periodic information processor configured to execute operational instructions for processing the digital vibration data, the operational instructions comprising instructions which, when executed:
generate a vibration waveform based on the digital vibration data;
perform an autocorrelation function on the vibration waveform to generate an autocorrelation waveform;
perform a Fast Fourier Transform on the vibration waveform to generate a vibration spectrum;
perform a Fast Fourier Transform on the autocorrelation waveform to generate an autocorrelation spectrum;
compile a first list of amplitude peaks from the vibration spectrum;
compile a second list of amplitude peaks from the autocorrelation spectrum;
match autocorrelation amplitude peaks in the second list with vibration amplitude peaks in the first list;
generate a peak list that includes each vibration amplitude peak to the peak list that matches an autocorrelation amplitude peak;
as vibration amplitude peaks are added to the peak list, determine a total amount of peak energy associated with the vibration amplitude peaks in the peak list; and
after the total amount of peak energy associated with the vibration amplitude peaks in the peak list exceeds a predetermined threshold, generate a periodic information plot comprising the vibration amplitude peaks in the peak list.
2. The apparatus of claim 1 wherein the periodic information processor generates the periodic information plot having at least 80% fewer data points than the vibration spectrum.
3. The apparatus of claim 1 wherein the predetermined threshold comprises a percent energy value, and wherein the periodic information processor is configured to execute operational instructions for calculating the percent energy value according to
% Energy of Original=Total energy of vibration spectrum×% Periodic Energy
wherein
%
Periodic
Energy
=
MaxPeak
(
after
first
3
%
of
autocorrelation
waveform
)
and wherein MaxPeak (after 3% of waveform) comprises a maximum absolute peak in the autocorrelation waveform occurring outside the first 3% of the autocorrelation waveform.
4. The apparatus of claim 1 wherein the vibration waveform is a PeakVue waveform.
5. The apparatus of claim 1 wherein the periodic information processor is configured to execute operational instructions to arrange the amplitude peaks in the first and second lists in order of descending amplitude, such that a largest amplitude peak is first and a smallest amplitude peak is last.
6. The apparatus of claim 1 wherein the periodic information processor is configured to execute operational instructions to classify the amplitude peaks as synchronous peaks and nonsynchronous peaks, to assign one or more first display colors to the synchronous peaks in the periodic information plot, and to assign one or more second display colors to the nonsynchronous peaks in the periodic information plot, wherein the first display colors are different from the second display colors.
7. The apparatus of claim 1 wherein the periodic information processor is configured to execute operational instructions to separate amplitude peaks that are synchronous peaks into multiple families and to assign a different display color to each family of synchronous peaks in the periodic information plot.
8. The apparatus of claim 1 further comprising:
a data communication network to which the periodic information processor is connected and through which the periodic information plot is communicated; and
an analyst computer connected to the data communication network, the analyst computer for receiving and displaying the periodic information plot for viewing by an analyst.
9. The apparatus of claim 1 wherein the periodic information processor determines a match between an autocorrelation amplitude peak from the second list and a vibration amplitude peak from the first list when
|vibration peak frequency−autocorrelation peak frequency|≤ n ×ΔFrequency,
where the vibration peak frequency is a frequency value of the vibration amplitude peak from the first list, the autocorrelation peak frequency is a frequency value of the autocorrelation amplitude peak from the second list, n is an integer value, and ΔFrequency is determined according to:
Δ
Frequency
=
F
max
of
vibration
spectrum
LOR
of
vibration
spectrum
,
where Fmax is the maximum frequency of the vibration spectrum and LOR is the number of lines of resolution in the vibration spectrum.
10. The apparatus of claim 1 wherein the data collector comprises a digital data recorder or a vibration data collector.
11. The apparatus of claim 1 wherein the data collector includes a low-pass anti-aliasing filter.
12. The apparatus of claim 1 wherein the periodic information processor is a component of the data collector.
13. The apparatus of claim 1 wherein the periodic information processor is a component of an analyst computer that is in communication with the data collector via a communication network.
14. An apparatus for acquiring and analyzing periodic information in vibration associated with a machine, the apparatus comprising:
a vibration sensor securely attached to the machine in a location providing a solid transmission path from a source of vibration within the machine to the vibration sensor, the vibration sensor for generating a vibration signal;
a data collector in communication with the vibration sensor, the data collector configured to receive and condition the vibration signal, the data collector comprising:
an analog-to-digital converter for converting the vibration signal to digital vibration data; and
memory for buffering the digital vibration data; and
a periodic information processor operable to receive the digital vibration data, the periodic information processor configured to execute operational instructions for processing the digital vibration data, the operational instructions comprising instructions which, when executed:
generate a vibration waveform based on the digital vibration data;
perform a Fast Fourier Transform on the vibration waveform to generate a vibration spectrum having amplitude values Y VS (n), where n=1 to N, and N is a number of frequency values;
perform an autocorrelation function on the a vibration waveform to generate an autocorrelation waveform;
perform a Fast Fourier Transform on the autocorrelation waveform to generate an autocorrelation spectrum having amplitude values Y AS (n), where n=1 to N, where N is the number of frequency values;
combine adjacent pairs of amplitude values Y VS (2n) and Y VS (2n−1) in the a vibration spectrum, according to
Y MCVS ( n )=√{square root over (( Y VS (2 n− 1)) 2 +( Y VS (2 n )) 2 )}; and
combine the a vibration spectrum and the autocorrelation spectrum to generate a periodic information plot having amplitude values Y PIP1 (n), according to
Y PIP1 ( n )= Y MCVS ( n )× Y AS ( n ), where n= 1 to N.
wherein inclusion of the amplitude values Y PIP1 (n) in the periodic information plot accentuates signal components that are pertinent to a diagnosis by an analyst while eliminating undesired non-periodic signal components, thereby improving visualization of pertinent signal components.
15. The apparatus of claim 14 wherein the periodic information processor is configured to execute operational instructions to generate a periodic information plot having amplitude values Y PIP3 (n), according to
If Y PIP1 ( n )> Y THR , Y PIP3 ( n )= Y PIP1 ( n )
If Y PIP1 ( n )≤ Y THR , Y PIP3 ( n )=0
where n=1 to N, and Y THR is a predetermined threshold value.
16. The apparatus of claim 14 wherein the periodic information processor is configured to execute operational instructions to perform an inverse Fast Fourier Transform on the periodic information plot to generate an information waveform.
17. The apparatus of claim 16 wherein the periodic information processor is configured to execute operational instructions to derive a circular information plot from the information waveform.
18. The apparatus of claim 14 wherein the periodic information processor is a component of the data collector.
19. The apparatus of claim 14 wherein the periodic information processor is a component of an analyst computer that is in communication with the data collector via a communication network.
20. An apparatus for acquiring and analyzing periodic information in vibration associated with a machine, the apparatus comprising:
a vibration sensor securely attached to the machine in a location providing a solid transmission path from a source of vibration within the machine to the vibration sensor, the vibration sensor for generating a vibration signal;
a data collector in communication with the vibration sensor, the data collector configured to receive and condition the vibration signal, the data collector comprising:
an analog-to-digital converter for converting the vibration signal to digital vibration data; and
memory for buffering the digital vibration data; and
a periodic information processor operable to receive the digital vibration data, the periodic information processor configured to execute operational instructions for processing the digital vibration data, the operational instructions comprising instructions which, when executed:
generate a vibration waveform based on the digital vibration data;
perform a Fast Fourier Transform on the vibration waveform to generate a vibration spectrum having amplitude values Y VS (n), where n=1 to M, and M is a number of frequency values;
perform an autocorrelation function on the vibration waveform to generate an autocorrelation waveform;
perform a Fast Fourier Transform on the autocorrelation waveform to generate an autocorrelation spectrum having amplitude values Y AS (n), where n=1 to N, where N is the number of frequency values;
combine adjacent pairs of amplitude values Y VS (2n) and Y VS (2n−1) in the vibration spectrum, according to
Y MCVS ( n )=√{square root over (( Y VS (2 n− 1)) 2 +( Y VS (2 n )) 2 )}; and
generate a periodic information plot having amplitude values Y PIP2 (n), according to
If Y AS ( n )> Y THR , Y PIP2 ( n )= Y MCVS ( n )
If Y AS ( n )≤ Y THR , Y PIP2 ( n )=0,
where n=1 to N, and Y THR is a predetermined threshold value,
wherein inclusion of only the amplitude values Y PIP2 (n) in the periodic information plot accentuates signal components that are pertinent to a diagnosis by an analyst, while eliminating undesired non-periodic signal components, thereby improving visualization of pertinent signal components.
21. The apparatus of claim 20 wherein the periodic information processor is a component of the data collector.
22. The apparatus of claim 20 wherein the periodic information processor is a component of an analyst computer that is in communication with the data collector via a communication network.
23. An apparatus for acquiring and analyzing periodic information in vibration associated with a machine, the apparatus comprising:
a vibration sensor securely attached to the machine in a location providing a solid transmission path from a source of vibration within the machine to the vibration sensor, the vibration sensor for generating a vibration signal;
a data collector in communication with the vibration sensor, the data collector configured to receive and condition the vibration signal, the data collector comprising:
an analog-to-digital converter for converting the vibration signal to digital vibration data; and
memory for buffering the digital vibration data; and
a periodic information processor operable to receive the digital vibration data, the periodic information processor configured to execute operational instructions for processing the digital vibration data, the operational instructions comprising instructions which, when executed:
generate a vibration waveform based on the digital vibration data;
perform a Fast Fourier Transform on the digital vibration data to generate a vibration spectrum having amplitude values Y VS (n), where n=1 to N, where N is a number of frequency values;
combine adjacent pairs of amplitude values Y VS (2n) and Y VS (2n−1) in the vibration spectrum, according to
Y MCVS ( n )=√{square root over (( Y VS (2 n− 1)) 2 +( Y VS (2 n )) 2 )};
perform an autocorrelation function on the vibration waveform to generate an autocorrelation waveform;
perform a Fast Fourier Transform on the autocorrelation waveform to generate an autocorrelation spectrum having amplitude values Y AS (n), where n=1 to N, where N is the number of frequency values; and
combine the vibration spectrum and the autocorrelation spectrum to generate a periodicity map having coordinate values X PM (n) and Y PM (n) determined according to
X PM ( n )= Y MCVS ( n )
Y PM ( n )= Y AS ( n )
for n=1 to N.
24. The apparatus of claim 23 wherein the periodic information processor is a component of the data collector.
25. The apparatus of claim 23 wherein the periodic information processor is a component of an analyst computer that is in communication with the data collector via a communication network.
26. An apparatus for acquiring and analyzing periodic information in vibration associated with a machine, the apparatus comprising:
a vibration sensor securely attached to the machine in a location providing a solid transmission path from a source of vibration within the machine to the vibration sensor, the vibration sensor for generating a vibration signal;
a data collector in communication with the vibration sensor, the data collector configured to receive and condition the vibration signal, the data collector comprising:
an analog-to-digital converter for converting the vibration signal to digital vibration data; and
memory for buffering the digital vibration data; and
a periodic information processor operable to receive the digital vibration data, the periodic information processor configured to execute operational instructions for processing the digital vibration data, the operational instructions comprising instructions which, when executed:
generate a vibration waveform based on the digital vibration data;
perform an autocorrelation function on the vibration waveform to generate an autocorrelation waveform;
perform a Fast Fourier Transform on the autocorrelation waveform to generate an autocorrelation spectrum having amplitude values Y AS (n), where n=1 to N;
generate a non-periodic information plot having amplitude values Y NPIP (n), according to
If Y AS ( n )< Y THR , Y NPIP ( n )= Y AS ( n )
If Y AS ( n )≥ Y THR ,Y NPIP ( n )=0,
where n=1 to N, and Y THR is a predetermined threshold value,
wherein inclusion of only the amplitude values Y NPIP (n) in the non-periodic information plot accentuates signal components that are pertinent to a diagnosis by an analyst, while eliminating undesired non-periodic signal components, thereby improving visualization of pertinent signal components.
27. The apparatus of claim 26 wherein the periodic information processor is a component of the data collector.
28. The apparatus of claim 26 wherein the periodic information processor is a component of an analyst computer that is in communication with the data collector via a communication network.
29. An apparatus for acquiring and analyzing periodic information in vibration associated with a machine, the apparatus comprising:
a vibration sensor securely attached to the machine in a location providing a solid transmission path from a source of vibration within the machine to the vibration sensor, the vibration sensor for generating a vibration signal;
a tachometer sensor configured to be attached to the machine and generate a turning speed;
a data collector in communication with the vibration sensor and the tachometer sensor, the data collector configured to receive and condition the vibration signal and the turning speed, the data collector comprising:
an analog-to-digital converter for converting the vibration signal to digital vibration data; and
memory for buffering the digital vibration data; and
a periodic information processor operable to receive the digital vibration data, the periodic information processor configured to execute operational instructions for processing the digital vibration data, the operational instructions comprising instructions which, when executed:
generate a vibration waveform based on the digital vibration data;
determine a maximum peak amplitude of the vibration waveform;
perform an autocorrelation function on the vibration waveform to generate an autocorrelation waveform;
determine a periodic signal parameter value based at least in part on the autocorrelation waveform, where the periodic signal parameter value comprises a single real number indicative of a level of periodic information in the vibration waveform;
calculate or receive a fault limit level; and
calculate one or more severity values based on the maximum peak amplitude and the fault limit level.
30. The apparatus of claim 29 wherein the periodic information processor is a component of the data collector.
31. The apparatus of claim 29 wherein the periodic information processor is a component of an analyst computer that is in communication with the data collector via a communication network.
32. The apparatus of claim 29 wherein the vibration waveform is a PeakVue waveform.
33. The apparatus of claim 29 wherein, if the periodic signal parameter value is greater than 0.1 or % Periodic Energy is greater than a predetermined percentage, and machine speed is unknown, the periodic information processor calculates a Bearing Fault Severity (BFS) value according to:
BFS
=
Normalized
Severity
×
%
Periodic
Energy
,
where
Normalized
Severity
=
Max
Peak
2
×
Fault
Limit
×
x
and
%
Periodic
Energy
=
Max
Peak
(
after
first
3
%
of
autocorrelation
wave
form
)
.
34. The apparatus of claim 29 wherein, if the periodic signal parameter value is greater than 0.1 or % Periodic Energy is greater than a predetermined percentage, and machine speed is known, the periodic information processor calculates a Bearing Fault Severity (BFS) value according to:
BFS
=
Normalized
severity
×
[
(
(
energy
of
the
located
nonsychronous
peaks
)
2
(
total
energy
of
the
associated
PeakVue
spectrum
)
2
)
]
where
Normalized
Severity
=
Max
Peak
2
×
Fault
Limit
×
x
.
wherein x is a normalization factor.
35. The apparatus of claim 29 further comprising the periodic information processor configured to execute operational instructions to calculate an alert limit level based on the turning speed, wherein if the periodic signal parameter value is less than 0.1 or % Periodic Energy is less than a predetermined percentage, and the maximum peak amplitude of the vibration waveform is greater than the alert limit level, the periodic information processor calculates a Lubrication Severity (LS) value according to:
LS
=
Max
Peak
2
×
Fault
Limit
×
x
×
%
NPE
,
wherein Percent Non-Periodic Energy (% NPE) is a function of Percent Periodic Energy (% Periodic Energy), and Percent Periodic Energy is calculated from the autocorrelation waveform according to:
%
Periodic
Energy
=
Max
Peak
(
after
first
3
%
of
autocorrelation
wave
form
)
.
36. The apparatus of claim 29 wherein, if the periodic signal parameter value is greater than 0.1 or % Periodic Energy is greater than a predetermined percentage, the periodic information processor executes operational instructions to calculate a Gearbox Fault Severity (GFS) value according to:
GFS
=
Normalized
Severity
×
[
(
(
energy
of
the
located
synchronous
peaks
)
2
(
total
energy
of
the
associated
PeakVue
spectrum
)
2
)
]
wherein
Normalized
Severity
=
General
Severity
×
x
and
General
Severity
=
Max
Peak
/
(
2
×
Fault
Limit
)
and
x
is
a
normalization
factor
.