Apparatus and method for compressing measurement data corelative to machine status

• US 6,507,804 B1
• Filed: 02/14/2000
• Issued: 01/14/2003
• Est. Priority Date: 10/14/1997
• Status: Expired due to Fees

• Current Assignee: BN Corporation LLC
• Original Assignee: Bently Nevada Incorporated (General Electric Company)
• Inventors: Tart, Michael Alan, Miguel, Joseph D., Hala, Roger A.
• Primary Examiner(s): WACHSMAN, HAL D
• Application Number:
  US09/503,644
• Time in Patent Office: 1,065 Days
• Field of Search: 702/182, 702/56, 702/33-35, 702/38, 702/41-44, 702/54, 702/70-72, 702/76, 702/77, 702/79, 702/103-106, 702/188, 702/124, 702/113-115, 702/126, 702/141, 702/180, 702/183-187, 702/189-191, 702/193-195, 702/198, 702/145-148, 702/FOR-123, 702/FOR.135, 702/FOR.136, 702/FOR.168, 702/FOR.171, 324/76.13, 324/76.15, 324/76.22, 324/76.33, 340/683, 340/870.16, 340/679, 340/680, 735/83, 735/79, 731/16, 736/59, 736/60, 735/70, 735/77, 735/78, 73/66, 735/82, 736/18, 734/57, 734/62, 73/11.4, 737/78, 73D/IG.1, 704/205, 704/500, 704/501, 704/503, 704/504, 704/201, 704/203, 704/224, 704/228, 700/73, 700/74, 700/275, 700/280, 700/279, 700/174, 700/175, 700/177, 708/203, 708/403
• US Class Current: 702/182
• CPC Class Codes: G01H 1/003 of rotating machines G01H1/10 takes precedence
• CPC Class Codes: G01N 29/14 using acoustic emission techniques echo of particles G01N29/046; measuring mechanical vibrations or acoustic waves in solids in general G01H1/00
• CPC Class Codes: G01N 29/4427 with stored values, e.g. threshold values
• CPC Class Codes: G01N 29/46 by spectral analysis, e.g. Fourier analysis or wavelet analysis spectral signal processing per se G06F17/14

Abstract

A method and apparatus for compressing, storing and transmitting measurement data correlative to machine status is disclosed in which the measurement data is continuously sensed, sampled and processed to extract significant spectral elements including magnitude and phase information from each successive period of the originally measured data and to store those spectral elements in a memory means from an initial period of significant spectral elements and each successive period of significant spectral elements which have changed since the previous period for developing a compressed data history correlative to a continuous history of the status of the machine being monitored and from which continuous signals can be regenerated and analyzed for any earlier historical time.

Claims

1. A method for compressing measurement data correlative to status of operation of a machine, the steps including:

monitoring a plurality of rotations of a rotating shaft of the machine;

determining a period of each of said plurality of rotations defining previous periods;

predicting a subsequent period of rotation of the rotating shaft as a function of said previous periods;

sensing machine data correlative to the status of operation of the machine;

sampling said sensed machine data at a sampling rate that is a function of said subsequent period;

transforming said sampled data into spectral elements;

comparing said spectral elements to a user definable criteria for retention; and

compressing said sampled data by storing in a memory means those spectral elements which have passed said user definable criteria for retention wherein said stored spectral elements are correlative to the status of operation of the machine.

2. A signal processing method for processing machinery signals correlative to status of operation of a machine, the steps including:

(a) monitoring periods of rotation of a rotating shaft of the machine;

(b) determining a last period of rotation of the rotating shaft from the monitored periods for defining a determined period;

(c) dividing the determined period into an integer number of smaller periods, one said smaller period defining a sampling period;

(d) sensing a signal correlative to the status of operation of the machine during a next period of rotation of the rotating shaft subsequent to said last period;

(e) sampling said sensed signal at a sampling rate that is a function of said sampling period, and

(f) storing said sampled sensed signal for obtaining data correlative to the status of operation of the machine.

3. The method of claim 2 further including the step of iteratively repeating steps (b) through (f) for an integer number of successive periods of rotation of the rotating shaft of the machine.

4. A signal processing method for processing machinery signals correlative to status of operation of a machine, the steps including:

(a) monitoring periods of rotation of a rotating shaft of the machine;

(b) determining a last period of rotation of the rotating shaft from the monitored periods for defining a first period;

(c) determining a previous period of rotation of the rotating shaft from the monitored periods that is immediately prior to said last period for defining a second period;

(d) predicting a next period of rotation of the rotating shaft subsequent to said last period as a function of both said first period and said second period for defining a predicted period of rotation of the rotating shaft;

(e) sensing a signal correlative to status of operation of the machine during said predicted next period;

(f) sampling said sensed signal at a sampling rate that is a function of said predicted next period, and

(g) processing said sampled sensed signal for obtaining data correlative to the status of operation of the machine.

5. The method of claim 4 wherein said step of predicting said next period of rotation of the rotating shaft subsequent to said last period as a function of both said first period and said second period for defining said predicted period includes the step of adding said first period to the difference between said first period and said second period for defining said predicted period of rotation of the rotating shaft.

6. The method of claim 5 wherein said step of sampling said sensed signal at said sampling rate that is the function of said predicted next period includes the step of sampling said sensed signal at a sampling rate that is a quotient resulting from a division of said predicted next period by a synchronous sampling rate.

7. The method of claim 6 wherein said step of sampling said sensed signal at said sampling rate that is said quotient resulting from said division of said predicted next period by said synchronous sampling rate includes the step of defining said synchronous sampling rate as a multiple of the rotating shaft speed.

8. The method of claim 4 further including the step of iteratively repeating steps (b) through (g) for an integer number of successive periods of rotation of the rotating shaft of the machine.

9. A method for compressing measurement data correlative to status of operation of a machine, the steps including:

determining a speed of a rotating shaft of a machine during each shaft revolution;

determining a sampling period as a function of the determined rotating shaft speed;

sensing machine data correlative to the status of operation of the machine;

sampling said sensed data at a sampling rate that is a function of said sampling period determined as the function of the determined rotating shaft speed;

transforming said sampled data into spectral elements;

comparing said spectral elements to a user definable criteria for retention; and

compressing said sampled data by storing in a memory means those spectral elements which have passed said user definable criteria for retention wherein said stored spectral elements are correlative to the status of operation of the machine.

10. A method for compressing measurement data correlative to status of operation of a machine, the steps including:

sensing a series of sets of machine data correlative to the status of operation of the machine;

sampling the series of sets of machine data;

applying a windowing function to the sampled series of sets of machine data;

transforming the windowed sampled series of sets of machine data into first intervals of spectral elements;

truncating at least one end of each of the first intervals of spectral elements;

transforming the windowed sampled series of sets of machine data into second intervals of spectral elements wherein the second intervals overlap the first intervals;

truncating at least one end of each of the second intervals of spectral elements;

comparing both the first and second intervals of spectral elements, absent the truncated ends, to a user definable criteria for retention; and

compressing the windowed sampled series of sets of machine data by storing in a memory means those spectral elements which have passed the user definable criteria for retention wherein the stored spectral elements are correlative to the status of operation of the machine.